Calculating speed and travel times with travel delays

ABSTRACT

Computer program products, methods, systems, apparatus, and computing entities are provided for forecasting travel delays corresponding to streets, street segments, geographic areas, geofenced areas, and/or user-specified criteria. And from the forecasted travel delays, speed and travel times that take into account such travel delays can be determined.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.13/940,699 filed Jul. 12, 2013, which is a continuation-in-part of U.S.application Ser. No. 13/436,083 filed Mar. 30, 2012, which claimspriority to U.S. Appl. No. 61/511,915 filed on Jul. 26, 2011, and toU.S. Appl. No. 61/470,185 filed on Mar. 31, 2011, all of which areherein incorporated by reference in their entireties.

BACKGROUND

Various needs exist for accurately determining speeds and travel timesthat take into account travel delays.

SUMMARY

In general, embodiments of the present invention provide methods,apparatus, systems, computing devices, computing entities, and/or thelike for determining an estimated travel time.

In accordance with one aspect, a method for determining an estimatedtravel time is provided. In one embodiment, the method comprises (1)identifying speed information associated with traveling from a firstlocation to a second location; (2) identifying distance informationassociated with traveling from the first location to the secondlocation; (3) identifying travel delay information associated withtraveling from the first location to the second location; and (4)determining an estimated time of travel time for traveling from thefirst location to the second location based at least in part on thespeed information, the distance information, and the travel delayinformation.

In accordance with another aspect, a computer program product fordetermining an estimated travel time is provided. The computer programproduct may comprise at least one computer-readable storage mediumhaving computer-readable program code portions stored therein, thecomputer-readable program code portions comprising executable portionsconfigured to (1) identify speed information associated with travelingfrom a first location to a second location; (2) identify distanceinformation associated with traveling from the first location to thesecond location; (3) identify travel delay information associated withtraveling from the first location to the second location; and (4)determine an estimated time of travel time for traveling from the firstlocation to the second location based at least in part on the speedinformation, the distance information, and the travel delay information.

In accordance with yet another aspect, an apparatus comprising at leastone processor and at least one memory including computer program code isprovided. In one embodiment, the at least one memory and the computerprogram code may be configured to, with the processor, cause theapparatus to (1) identify speed information associated with travelingfrom a first location to a second location; (2) identify distanceinformation associated with traveling from the first location to thesecond location; (3) identify travel delay information associated withtraveling from the first location to the second location; and (4)determine an estimated time of travel time for traveling from the firstlocation to the second location based at least in part on the speedinformation, the distance information, and the travel delay information.

In accordance with one aspect, a method for determining an average speedis provided. In one embodiment, the method comprises (1) identifyingtelematics data associated with a vehicle that traveled from an originlocation to an end location; (2) identifying an indication of a loss oflocation information associated with a first intermediate location andan indication of an acquisition of location information associated witha second intermediate location, the first and second intermediatelocations traveled en route from the origin location to the endlocation; (3) determining a distance traveled from the origin locationto the end location, the distance traveled excluding the distancetraveled from the first intermediate location and the secondintermediate location; (4) determining an estimated time of travel timefor traveling from the origin location to the end location, theestimated time of travel excluding the time of travel from the firstintermediate location and the second intermediate location; and (5)determining an average speed for traveling from the origin location tothe end location based at least in part on the distance traveled and theestimated time of travel time.

In accordance with another aspect, a computer program product fordetermining an average speed is provided. The computer program productmay comprise at least one computer-readable storage medium havingcomputer-readable program code portions stored therein, thecomputer-readable program code portions comprising executable portionsconfigured to (1) identify telematics data associated with a vehiclethat traveled from an origin location to an end location; (2) identifyan indication of a loss of location information associated with a firstintermediate location and an indication of an acquisition of locationinformation associated with a second intermediate location, the firstand second intermediate locations traveled en route from the originlocation to the end location; (3) determine a distance traveled from theorigin location to the end location, the distance traveled excluding thedistance traveled from the first intermediate location and the secondintermediate location; (4) determine an estimated time of travel timefor traveling from the origin location to the end location, theestimated time of travel excluding the time of travel from the firstintermediate location and the second intermediate location; and (5)determine an average speed for traveling from the origin location to theend location based at least in part on the distance traveled and theestimated time of travel time.

In accordance with yet another aspect, an apparatus comprising at leastone processor and at least one memory including computer program code isprovided. In one embodiment, the at least one memory and the computerprogram code may be configured to, with the processor, cause theapparatus to (1) identify telematics data associated with a vehicle thattraveled from an origin location to an end location; (2) identify anindication of a loss of location information associated with a firstintermediate location and an indication of an acquisition of locationinformation associated with a second intermediate location, the firstand second intermediate locations traveled en route from the originlocation to the end location; (3) determine a distance traveled from theorigin location to the end location, the distance traveled excluding thedistance traveled from the first intermediate location and the secondintermediate location; (4) determine an estimated time of travel timefor traveling from the origin location to the end location, theestimated time of travel excluding the time of travel from the firstintermediate location and the second intermediate location; and (5)determine an average speed for traveling from the origin location to theend location based at least in part on the distance traveled and theestimated time of travel time.

In accordance with one aspect, a method for determining a fee isprovided. In one embodiment, the method comprises (1) determining adistance traveled by a vehicle within a geographical area during one ormore time periods, the determining based at least in part on operationaldata comprising vehicle telematics data indicative of one or morevehicle dynamics for the vehicle during the one or more time periods;(2) determining the duration of one or more travel delay segmentsassociated with the geographical area during the one or more timeperiods based at least in part on the operational data; (3) determininga value indicative of the average amount of travel delay time per unitof distance within the geographical area based at least in part on thedistance traveled and the duration of the travel delay segments; and (4)determining a fee associated with the geographical area based at leastin part on the value indicative of the average amount of travel delaytime per unit of distance within the geographical area.

In accordance with another aspect, a computer program product fordetermining a fee is provided. The computer program product may compriseat least one computer-readable storage medium having computer-readableprogram code portions stored therein, the computer-readable program codeportions comprising executable portions configured to (1) determine adistance traveled by a vehicle within a geographical area during one ormore time periods, the determining based at least in part on operationaldata comprising vehicle telematics data indicative of one or morevehicle dynamics for the vehicle during the one or more time periods;(2) determine the duration of one or more travel delay segmentsassociated with the geographical area during the one or more timeperiods based at least in part on the operational data; (3) determine avalue indicative of the average amount of travel delay time per unit ofdistance within the geographical area based at least in part on thedistance traveled and the duration of the travel delay segments; and (4)determine a fee associated with the geographical area based at least inpart on the value indicative of the average amount of travel delay timeper unit of distance within the geographical area.

In accordance with yet another aspect, an apparatus comprising at leastone processor and at least one memory including computer program code isprovided. In one embodiment, the at least one memory and the computerprogram code may be configured to, with the processor, cause theapparatus to (1) determine a distance traveled by a vehicle within ageographical area during one or more time periods, the determining basedat least in part on operational data comprising vehicle telematics dataindicative of one or more vehicle dynamics for the vehicle during theone or more time periods; (2) determine the duration of one or moretravel delay segments associated with the geographical area during theone or more time periods based at least in part on the operational data;(3) determine a value indicative of the average amount of travel delaytime per unit of distance within the geographical area based at least inpart on the distance traveled and the duration of the travel delaysegments; and (4) determine a fee associated with the geographical areabased at least in part on the value indicative of the average amount oftravel delay time per unit of distance within the geographical area.

In accordance with one aspect, a method for determining an average speedis provided. In one embodiment, the method comprises (1) identifyingtime information associated with traveling from a first location to asecond location; (2) identifying distance information associated withtraveling from the first location to the second location; (3)identifying travel delay information associated with traveling from thefirst location to the second location; and (4) determining an averagespeed for traveling from the first location to the second location basedat least in part on the time information, the distance information, andthe travel delay information.

In accordance with another aspect, a computer program product fordetermining an average speed is provided. The computer program productmay comprise at least one computer-readable storage medium havingcomputer-readable program code portions stored therein, thecomputer-readable program code portions comprising executable portionsconfigured to (1) identify time information associated with travelingfrom a first location to a second location; (2) identify distanceinformation associated with traveling from the first location to thesecond location; (3) identify travel delay information associated withtraveling from the first location to the second location; and (4)determine an average speed for traveling from the first location to thesecond location based at least in part on the time information, thedistance information, and the travel delay information.

In accordance with yet another aspect, an apparatus comprising at leastone processor and at least one memory including computer program code isprovided. In one embodiment, the at least one memory and the computerprogram code may be configured to, with the processor, cause theapparatus to (1) identify time information associated with travelingfrom a first location to a second location; (2) identify distanceinformation associated with traveling from the first location to thesecond location; (3) identify travel delay information associated withtraveling from the first location to the second location; and (4)determine an average speed for traveling from the first location to thesecond location based at least in part on the time information, thedistance information, and the travel delay information.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

Having thus described the invention in general terms, reference will nowbe made to the accompanying drawings, which are not necessarily drawn toscale, and wherein:

FIG. 1 is a block diagram of an efficiency management system accordingto various embodiments of the present invention;

FIG. 2 is a block diagram of a fleet management system according tovarious embodiments of the present invention;

FIG. 3 is a block diagram of a telematics device according to oneembodiment of the present invention;

FIG. 4 is a block diagram of a block diagram of a mobile deviceaccording to one embodiment of the present invention;

FIG. 5 is a schematic block diagram of a central server according to oneembodiment of the present invention;

FIG. 6 is a flow diagram of steps executed by the telematics deviceaccording to one embodiment of the present invention;

FIG. 7 is a flow diagram of steps executed by the mobile deviceaccording to one embodiment of the present invention;

FIG. 8 shows a start-up view of a central server graphical userinterface according to one embodiment of the present invention;

FIG. 9 is a flow diagram of steps executed by the central serveraccording to one embodiment of the present invention;

FIG. 10 is a flow diagram of steps executed by a data segmenting moduleaccording to one embodiment of the present invention;

FIG. 11 shows a Gantt chart of activity segments according to oneembodiment of the present invention;

FIG. 12 shows a flow diagram of steps executed by an employee recapmodule according to one embodiment of the present invention;

FIG. 13 shows an employee recap view of a central server graphical userinterface according to one embodiment of the present invention;

FIG. 14 shows an employee recap report according to one embodiment ofthe present invention;

FIG. 15 shows a flow diagram of steps executed by an employee timecardmodule according to one embodiment of the present invention;

FIG. 16 shows an employee timecard view of a central server graphicaluser interface according to one embodiment of the present invention;

FIG. 17 shows an employee timecard report according to one embodiment ofthe present invention;

FIG. 18 shows a flow diagram of steps executed by an employee Ganttmodule according to one embodiment of the present invention;

FIG. 19 shows an employee Gantt view of a central server graphical userinterface according to one embodiment of the present invention;

FIG. 20 shows a flow diagram of steps executed by an employee delay codemodule according to one embodiment of the present invention;

FIG. 21 shows an employee delay code view of a central server graphicaluser interface according to one embodiment of the present invention;

FIG. 22 shows a flow diagram of steps executed by an employee fueleconomy module according to one embodiment of the present invention;

FIG. 23 shows an employee fuel economy view of a central servergraphical user interface according to one embodiment of the presentinvention;

FIG. 24 shows an employee fuel economy report according to oneembodiment of the present invention;

FIG. 25 shows a flow diagram of steps executed by an employee tracemodule according to one embodiment of the present invention;

FIG. 26 shows an employee trace view of a central server graphical userinterface according to one embodiment of the present invention;

FIG. 27 shows a flow diagram of steps executed by a location performancemodule according to one embodiment of the present invention;

FIG. 28 shows a location performance view of a central server graphicaluser interface according to one embodiment of the present invention;

FIG. 29 shows a flow diagram of steps executed by a location hoursmodule according to one embodiment of the present invention;

FIG. 30 shows a location hours view of a central server graphical userinterface according to one embodiment of the present invention;

FIG. 31 shows a flow diagram of steps executed by a location idle timemodule according to one embodiment of the present invention;

FIG. 32 shows a location idle time view of a central server graphicaluser interface according to one embodiment of the present invention;

FIG. 33 shows a location idle time report according to one embodiment ofthe present invention;

FIG. 34 shows a flow diagram of steps executed by a location delay codemodule according to one embodiment of the present invention;

FIG. 35 shows a location delay code view of a central server graphicaluser interface according to one embodiment of the present invention;

FIG. 36 shows a flow diagram of steps executed by a location stop moduleaccording to one embodiment of the present invention;

FIG. 37 shows a location stop view of a central server graphical userinterface according to one embodiment of the present invention;

FIG. 38 shows a flow diagram of steps executed by a location dispatchprofile module according to one embodiment of the present invention;

FIG. 39 shows a location dispatch profile view of a central servergraphical user interface according to one embodiment of the presentinvention;

FIG. 40 shows an employee safety view of a central server graphical userinterface according to one embodiment of the present invention;

FIG. 41 shows an employee work area view of a central server graphicaluser interface according to one embodiment of the present invention;

FIG. 42 shows a location safety view of a central server graphical userinterface according to one embodiment of the present invention;

FIG. 43 shows a polygon map selection tool provided on a central servergraphical user interface according to one embodiment of the presentinvention;

FIG. 44 shows a multiple window tool provided on a central servergraphical user interface according to one embodiment of the presentinvention;

FIG. 45 shows a road traveled by a delivery vehicle according to oneembodiment of the present invention;

FIG. 46 shows a string of road data points representing the road of FIG.45 according to one embodiment of the present invention;

FIG. 47 shows a string of location data points representing the path ofa vehicle along the road of FIG. 45 according to one embodiment of thepresent invention;

FIG. 48 shows an unknown road adjacent the road of FIG. 45 according toone embodiment of the present invention;

FIG. 49 shows a string of location data points representing the path ofa vehicle along the unknown road according to one embodiment of thepresent invention;

FIG. 50 shows a new path comprised of the location data points of FIG.49 according to one embodiment of the present invention; and

FIG. 51 shows a flow diagram of steps executed by a map update moduleaccording to one embodiment of the present invention.

FIGS. 52-63 show exemplary input and output according to one embodimentof the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The present inventions now will be described more fully hereinafter withreference to the accompanying drawings, in which some, but not allembodiments of the inventions are shown. Indeed, these inventions may beembodied in many different forms and should not be construed as limitedto the embodiments set forth herein; rather, these embodiments areprovided so that this disclosure will satisfy applicable legalrequirements. Like numbers refer to like elements throughout.

Many modifications and other embodiments of the inventions set forthherein will come to mind to one skilled in the art to which theseinventions pertain having the benefit of the teachings presented in theforegoing descriptions and the associated drawings. Therefore, it is tobe understood that the inventions are not to be limited to the specificembodiments disclosed and that modifications and other embodiments areintended to be included within the scope of the appended claims.Although specific terms are employed herein, they are used in a genericand descriptive sense only and not for purposes of limitation.

Overview

According to various embodiments of the present invention, an efficiencymanagement system is provided for evaluating various operationalefficiencies based on operational data. FIG. 1 illustrates the systemarchitecture of an efficiency management system 1 according to variousembodiments. As shown, the efficiency management system 1 includes oneor more data sources 2 and a central server 3. The data sources 2 maybe, for example, devices configured for capturing and communicatingoperational data indicative of one or more operational characteristics(e.g., a telematics device capturing telematics data from a vehicle, aservice device capturing service data from vehicle operators, a computertracking the activity of one or more users). The data sources 2 areconfigured to communicate with the central server 3 by sending andreceiving operational data over a network 4 (e.g., the Internet, anIntranet, or other suitable network). The central server 3 is configuredto process and evaluate operational data received from the data sources2 in accordance with user input received via a user interface (e.g., agraphical user interface provided on a local or remote computer). Forexample, the central server 3 may be configured for segmentingoperational data according to various operational activities,identifying various undesirable or inefficient activities or occurrencesbased on the operational data, and/or generating a graphicalpresentation based on the operational data that displays operationalactivities in the context of other efficiency-indicative data.

As discussed in greater detail below, the components and general systemarchitecture of the efficiency management system 1 illustrated in FIG. 1may be adapted for use in specific environments. For example, in certainembodiments, the efficiency management system is configured as a “fleetmanagement system” adapted for evaluating and managing a fleet ofvehicles (e.g., a fleet of delivery vehicles operated by a shippingentity, a fleet of taxis or buses operated by a private or publictransportation entity). In such embodiments, the data sources maycomprise telematics devices positioned on various vehicles in the fleet,as well as mobile service devices operated at least in part by operatorsof the fleet vehicles. The central server may be configured forevaluating telematics data received from the telematics devices andservice data received from the service devices in order to assess driverefficiency, vehicle efficiency, and other logistical efficiencies. Inaddition, the central server may be configured for providing graphicalpresentations of telematics data and/or service data inefficiency-indicative formats, as well as for updating GPS-based mapsbased on vehicle telematics data.

In other embodiments, the efficiency management system is configured asa “mobile personnel management system” adapted for evaluating andmanaging human resource efficiencies. For example, in one embodiment,the mobile personnel management system is configured for evaluatingefficiencies of mobile employees or staff (e.g., employees at an airportor large store) based at least in part on data indicative of employeelocation and activity in relation to time. In such embodiments, the datasources may comprise location-indicating devices carried by variousemployees (e.g., GPS or RFID-based devices). The central server may beconfigured for evaluating data received from the location-indicatingdevices in order to determine whether employees are working efficientlybased at least in part on their location at various times.

In other embodiments, the efficiency management system is configured asa “personnel work management system” adapted for evaluating employee orstaff efficiencies based on data indicative of activity and time (e.g.,the efficiency of lawyers in relation to certain tasks). In suchembodiments, the data sources may comprise task-indicating devices(e.g., a computer with time-keeping software), while the central serveris configured for evaluating data received from the task-indicatingdevices in order to assess employee efficiency in relation to varioustasks or activities.

The following description provides a detailed explanation of certainembodiments of the efficiency management system, including theaforementioned fleet management system, mobile personnel managementsystem, and personnel work management system. As will be appreciatedfrom the detailed description herein, the various components andfeatures of these systems may be modified and adapted to assessefficiencies in a variety of operational contexts.

Fleet Management System

According to various embodiments, a fleet management system is providedfor capturing and storing operational data for a fleet of vehicles, andfor evaluating the operational data in order to assess various fleetefficiencies and improve the overall operational efficiency of thefleet. The fleet management system may be used, for example, by ashipping entity (e.g., United Parcel Service, Inc., FedEx Corp., or theUnited States Postal Service) to evaluate the efficiency of a fleet ofvehicles used to deliver freight or packages. In particular, the fleetmanagement system may be configured to capture operational data from thefleet—including telematics data from fleet vehicles and service datafrom service devices—and evaluate the captured operational data in orderto identify potentially inefficient or undesirable driver behavior, andto provide a unique graphical presentation of the telematics data andservice data indicative of identified behavior that allows system usersto understand the context in which the behavior occurred. As describedin more detail below, these system attributes allow the fleet managementsystem to assist vehicle fleet managers, such as shipping entities, inimproving the operating efficiency of their fleet.

System Architecture

A fleet management system 5 according to various embodiments is shown inFIG. 2. In the illustrated embodiment, the fleet management system 5comprises a vehicle telematics device 102 positioned on a deliveryvehicle 100, a mobile device 110, and a central server 120. Thetelematics device 102, mobile device 110, and central server 120 areconfigured to communicate with each other via a communications network130 (e.g., the Internet, an Intranet, a cellular network, or othersuitable network). In addition, the telematics device 102, mobile device110, and central server 120 are configured for storing data to anaccessible central server database (not shown) located on, or remotelyfrom, the central server 120.

In the description provided herein, the fleet management system 5 may beconfigured for managing and evaluating the operation of a large fleet ofdelivery vehicles. As such, in various embodiments, the fleet managementsystem 5 may further comprise a plurality of telematics devices 102 andmobile devices 110, each being associated with one of a plurality ofdelivery vehicles 100. While the detailed description of the fleetmanagement system's components is provided below with reference toindividual components or devices, it will be understood from thedescription herein that various embodiments of the fleet managementsystem 5 may include a plurality of the components each configured asdescribed below. For example, large-scale embodiments of the fleetmanagement system may include thousands of telematics devices 102 andmobile devices 110 each capturing data from a unique delivery vehicle100 or driver and transmitting the captured data to multiple servers120. In addition, as will be appreciated from the description herein,the fleet management system 5 may be adapted for managing and evaluatinga fleet of vehicles in a variety of contexts, such as a fleet of taxis,buses, and other service vehicles. Accordingly, the telematics device102 represents one embodiment of a telematics device that may be adaptedfor providing telematics data for a fleet of vehicles, and the mobiledevice 110 represents one embodiment of a service device that may beadapted for providing service data for a fleet of vehicles.

In the illustrated embodiment of FIG. 2, the delivery vehicle 100includes a plurality of vehicle sensors, readers, cameras, and/or thelike configured for generating and/or collecting telematics dataindicative of various vehicle dynamics, such as engine ignition, enginespeed, vehicle speed, vehicle location, and the status of variousvehicle components. The vehicle sensors may be controlled by thetelematics device 102, which may be positioned on or within the vehicle100. In controlling the various vehicle sensors, the telematics device102 is able to capture and store telematics data from the variousvehicle sensors according to a programmed logic and associate thecaptured telematics data with contextual data (e.g., date, time,location). The captured telematics data and contextual data may then betransmitted by the telematics device 102 directly to the central server120 via the network 130, or to the mobile device 110 (which may latertransmit the data to the central server 120 itself).

The mobile device 110 is a handheld electronic device—such as a pocketPC, delivery information acquisition device (DIAD), laptop, orsmartphone—that may be operated by a driver of the delivery vehicle 100.The mobile device 110 may be configured for receiving and displayingdelivery information received from the central server 120 (e.g.,delivery instructions pertaining to the delivery of freight or packages)and may be configured for receiving and storing telematics data receivedfrom the telematics device 102 as necessary. In addition, the mobiledevice 110 is configured for receiving and storing service datagenerated by user input (e.g., service data input by a driver via a userinterface indicating the status of a particular delivery or driveractivity). Furthermore, the mobile device 110 is configured fortransmitting any received data to the central server 120 and/ortelematics device 102 over the network 130.

According to various embodiments, the central server 120 may generallybe configured for evaluating operational data (e.g., telematics data,service data) for a fleet of vehicles in order to assess various fleetefficiencies and aid fleet management system 5 users in managing thefleet. As shown in FIG. 2, the central server 120 may be configured forreceiving and storing telematics data from the telematics device 102 andservice data from the mobile device 110 over the network 130. Bycollecting such operational data over a period of time from varioustelematics devices 102 and mobile devices 110—which may be associatedwith a fleet of vehicles 100 and their respective drivers—the centralserver 120 is able to amass operational data reflecting the overalloperations of the fleet. As will be described in greater detail below,the central server 120 may be configured for evaluating telematics dataand service data together, presenting the data to a user in the contextof one another, and evaluating the data in a variety of ways in order toimprove the operating efficiency of the fleet of vehicles 100.

The various components of the fleet management system 5 are nowdescribed in detail below according to various embodiments.

Network

According to various embodiments of the present invention, thecommunications network 130 may be capable of supporting communication inaccordance with any one or more of a number of second-generation (2G),2.5G and/or third-generation (3G) mobile communication protocols or thelike. More particularly, the network 130 may be capable of supportingcommunication in accordance with 2G wireless communication protocolsIS-136 (TDMA), GSM, and IS-95 (CDMA). Also, for example, the network 130may be capable of supporting communication in accordance with 2.5Gwireless communication protocols GPRS, Enhanced Data GSM Environment(EDGE), or the like. In addition, for example, the network 130 can becapable of supporting communication in accordance with 3G wirelesscommunication protocols such as Universal Mobile Telephone System (UMTS)network employing Wideband Code Division Multiple Access (WCDMA) radioaccess technology. As yet another example, the network 130 may supportcommunication between the fleet management system 5 components (e.g.,the telematics device 102 and mobile device 110) in accordance withtechniques such as, for example, radio frequency (RF), Bluetooth™,infrared (IrDA), or any of a number of different wireless networkingtechniques, including Wireless LAN (WLAN) techniques.

Although the telematics device 102, mobile device 110, and centralserver 120 are illustrated in FIG. 2 as communicating with one anotherover the same network 130, these devices may likewise communicate overseparate networks. For example, while the telematics device 102 maycommunicate with the mobile device 110 over a wireless personal areanetwork (WPAN) (e.g., using Bluetooth™ techniques), the telematicsdevice 102 and/or mobile device 110 may communicate with the centralserver 120 over a wireless wide area network (WWAN) (e.g., in accordancewith EDGE, or some other 2.5G, 3G, or 4G wireless communicationprotocol).

Vehicle Sensors

As noted above, in various embodiments the delivery vehicle 100 isequipped with a variety of vehicle sensors capable of generating vehicletelematics data. For example, in one embodiment, the vehicle 100includes sensors configured to make measurements and capture datapertaining to the following vehicle dynamics: engine ignition (e.g., onor off), engine speed (e.g., RPM and idle time events), vehicle speed(e.g., miles per hour), seat belt status (e.g., engaged or disengaged),vehicle heading (e.g., degrees from center), vehicle backing (e.g.,moving in reverse or not moving in reverse), vehicle door status (e.g.,open or closed), vehicle handle status (e.g., grasped or not grasped bya driver), vehicle location (e.g., latitude and longitude), distancetraveled (e.g., miles between two points), throttle position, brakepedal position, parking brake position, distance or time since lastmaintenance, and various engine measurements (e.g., engine oil pressure,engine temperature, and engine faults). In various other embodiments,the delivery vehicle 100 may include any combination of theabove-referenced sensors (and additional sensors known in the art)depending on the operational data desired by a fleet management system 5user.

According to various embodiments, the vehicles sensors disposed withinthe delivery vehicle 100 comprise on/off sensors, which register avoltage amount that corresponds with an on/off condition. For example,in one embodiment, a seat belt sensor may register 0V when the seat beltis disengaged and 12V when the seat belt is engaged. Such on/off sensorsare sufficient for measuring vehicle dynamics in which operational datais needed to indicate two conditions, such as a seat belt, which iseither engaged or disengaged at all times. As another example, one ormore door position sensors may be connected, for example, to the driverside, passenger side, and bulkhead doors, and may register 0V when thedoor with which the sensor is associated is in an open position, and 12Vwhen the door is closed. As another example, an ignition sensor mayregister 0V when the vehicle 100 is turned off and 12V when the vehicle100 is turned on. As yet another example, a backing light sensor mayregister 0V when the vehicles' backing lights are off and 12V when thevehicle's backing lights are on. As yet another example, the engine idlesensor may be configured to generate 0V when the engine speed is aboveidle and 12V when the engine is idling.

In addition, according to various embodiments, the vehicle sensorsdisposed within the delivery vehicles 100 also comprise variable voltagesensors, which may be used to register variations in voltage reflectinga certain vehicle dynamic. For example, the engine speed sensor maydetect the speed of the engine in revolutions per minute (RPM) byregistering a particular voltage that corresponds to a particular RPMreading. The voltage of the sensor may increase or decreaseproportionately with increases or decreases in the engine RPM. Asanother example, oil pressure sensors may detect the vehicle's oilpressure by registering a particular voltage that corresponds to aparticular oil pressure. Other examples of variable voltage sensors mayinclude temperature sensors, vehicle speed sensors, vehicle headingsensors, and vehicle location sensors.

The exemplary vehicle sensors described above may be configured, forexample, to operate in any fashion suitable to generatecomputer-readable data that may be captured, stored, and transmitted bythe telematics device 102. In addition, while certain sensors arepreferably disposed at particular locations on or within the vehicles100 (e.g., handle sensors at the vehicle handles), other sensors may bedisposed anywhere within the vehicle, such as within the telematicsdevice 102 itself (e.g., a location sensor).

Telematics Device

As noted above, according to various embodiments, the telematics device102 is configured to control various vehicle sensors positioned on anassociated delivery vehicle 100, capture vehicle telematics datagenerated by those sensors, and transmit the captured telematics data tothe mobile device 110 and/or central server 120 via one of severalcommunication methods. According to various embodiments, the variousfunctions of the telematics device 102 described herein may be generallyunderstood as being performed by one or more of the telematics device102 components described below.

FIG. 3 illustrates a detailed schematic block diagram of an exemplarytelematics device 102 according to one embodiment. In the illustratedembodiment, the telematics device 102 includes the following components:a processor 201, a location-determining device or sensor 202 (e.g., GPSsensor), a real-time clock 203, J-Bus protocol architecture 204, anelectronic control module (ECM) 205, a port 206 for receiving data fromvehicle sensors 410 located in one of the delivery vehicles 100 (shownin FIG. 2), a communication port 207 for receiving instruction data, aradio frequency identification (RFID) tag 212, a power source 208, adata radio 209 for communication with a WWAN, a WLAN and/or a WPAN,FLASH, DRAM, and NVRAM memory modules 210, and a programmable logiccontroller (PLC) 211. In an alternative embodiment, the RFID tag 212,the location sensor 202, and the PLC 211 may be located in the deliveryvehicle 100, external from the telematics device 102. In otherembodiments, the processes described herein as being carried out by asingle processor 201 may be accomplished by multiple processors. Invarious embodiments, the telematics device 102 may not include certainof the components described above, and may include any other suitablecomponents in addition to, or in place of, those described above. Forexample, the telematics device 102 may include various types ofcommunications components other than those described above (e.g., tosupport new or improved communications techniques).

In one embodiment, the location sensor 202 may be one of severalcomponents available in the telematics device 102. The location sensor202 may be, for example, a GPS-based sensor compatible with a low Earthorbit (LEO) satellite system, medium Earth orbit satellite system, or aDepartment of Defense (DOD) satellite system. Alternatively,triangulation may be used in connection with various cellular towerspositioned at various locations throughout a geographic area in order todetermine the location of the delivery vehicle 100 and/or its driver.The location sensor 202 may be used to receive position, time, and speedinformation/data. In addition, the location sensor 202 may be configuredto detect when its delivery vehicle 100 has entered or exited aGPS-defined geographic area (e.g., a geo-fenced area). As will beappreciated from the description herein, more than one location sensor202 may be utilized, and other similar techniques may likewise be usedto collect geo-location information associated with the delivery vehicle100 and/or its driver.

In one embodiment, the ECM 205 with J-Bus protocol 204 may be one ofseveral components available in the telematics device 102. The ECM 205,which may be a scalable and subservient device to the telematics device102, may have data processor capability to decode and store analog anddigital inputs and ECM data streams from vehicle systems and sensors410, 420. The ECM 205 may further have data processing capability tocollect and present vehicle data to the J-Bus 204 (which may allowtransmittal to the telematics device 102), and output standard vehiclediagnostic codes when received from a vehicle's J-Bus-compatibleon-board controllers 420 or vehicle sensors 410.

In one embodiment, the instruction data receiving port 207 may be one ofseveral components available in the telematics device 102. Embodimentsof the instruction data receiving port 207 may include an Infrared DataAssociation (IrDA) communication port, a data radio, and/or a serialport. The instruction receiving data port 207 may receive instructionsfor the telematics device 102. These instructions may be specific to thevehicle 100 in which the telematics device 102 is installed, specific tothe geographical area in which the vehicle 100 will be traveling, orspecific to the function the vehicle 100 serves within the fleet.

In one embodiment, an RFID tag 212 may be one of several componentsavailable for use with the telematics device 102. One embodiment of theRFID tag 212 may include an active RFID tag, which comprises at leastone of the following: (1) an internal clock; (2) a memory; (3) amicroprocessor; and (4) at least one input interface for connecting withsensors located in the vehicle 100 or the telematics device 102. Anotherembodiment of the RFID tag 212 may be a passive RFID tag. One or moreRFID tags 212 may be internal to the telematics device 102, wired to thetelematics device 102, and/or proximate to the telematics device 102.Each RFID tag 212 may communicate wirelessly with RFID interrogatorswithin a certain geographical range of each other. RFID interrogatorsmay be located external to the vehicle 100 and/or within the mobiledevice 110 that can be carried in and out of the vehicle 100 by thevehicle operator.

Further, in particular embodiments, the vehicle 100 may also include oneor more imaging devices in communication with, associated with, or aspart of the telematics device 102. For example, the imaging devices maybe disposed on a particular side of the vehicle 100 and/or located atthe front and rear of the vehicle 100. The front imaging device may befacing towards the rear of the vehicle 100 and may be angled to capturevehicles passing the vehicle 100 and/or other imagery (e.g., signs orstop lights) on the particular side the imaging device is mounted. Therear imaging device may be facing towards the front of the vehicle 100and may also be angled to allow for the proper capturing of images ofvehicles passing the vehicle 100 and/or other imagery (e.g., signs orstop lights) on the particular side the imaging device is mounted. Inaddition, the imaging device may be mounted at a height with respect tothe vehicle 100 to allow for the proper capturing of images of vehiclespassing the vehicle 100 and/or other imagery (e.g., signs or stoplights).

In one embodiment, the imaging devices may be analog or digital cameras(or video cameras or combinations thereof) for capturing images (e.g.,image data). It should be noted that the images and image data arereferred to herein as telematics data. That is, the telematics data mayinclude image data and/or images. For example, the imaging devices maybe cameras with wide angle lenses and/or cameras with narrow anglelenses. In one embodiment, the imaging devices may be dual-view imagingdevices that simultaneously record/capture images and/or video atdifferent lines of sight. The imaging devices may be configured tocontinuously record/capture images and/or video. Similarly, the imagingdevices may be configured to automatically record/capture and stoprecording/capturing image data upon the occurrence of certain specifiedevents, such as to determine when the vehicle is stopped.

The resolution of the images (e.g., image data) captured by the imagingdevice may be, for instance, 640 pixels by 480 pixels or higher. In oneembodiment, for night operation, the imaging devices may have asensitivity of 0.5 lux or better at an optical stop equivalent of F1.Further, the imaging devices may include or be used in association withvarious lighting, such as light emitting diodes (LEDs), Infrared lights,array lights, strobe lights, and/or other lighting mechanisms tosufficiently illuminate the zones of interest to capture image data foranalysis. The image data can be captured in or converted to a variety offormats, such as Joint Photographic Experts Group (JPEG), Motion JPEG(MJPEG), Moving Picture Experts Group (MPEG), Graphics InterchangeFormat (GIF), Portable Network Graphics (PNG), Tagged Image File Format(TIFF), bitmap (BMP), H.264, H.263, Flash Video (FLV), Hypertext MarkupLanguage 5 (HTML5), VP6, VP8, and/or the like.

In one embodiment, the imaging devices may include one or moreprocessors, one or more temporary memory storage areas, and/or one ormore permanent memory storage areas. For instance, the imaging devicescan capture (and timestamp) images (e.g., image data) and store themtemporarily in a buffer or permanently in memory storage areas within orexternal to the imaging devices. In one embodiment, the imaging devicesmay include, be associated with, or be in communication with a networkinterface for communicating with various entities. As indicated above,this communication may be via the same or different wired or wirelessnetworks using a variety of wired or wireless transmission protocols.

In one embodiment, the data radio 209 may be one of several componentsavailable in the telematics device 102. The data radio 209 may beconfigured to communicate with a WWAN, WLAN, or WPAN, or any combinationthereof. In one embodiment, a WPAN data radio provides connectivitybetween the telematics device 102 and peripheral devices used in closeproximity to the vehicle 100, such as the mobile device 110, a localcomputer, and/or a cellular telephone. As mentioned above, in oneembodiment of the invention, a WPAN, such as, for example, a Bluetooth™network (IEEE 802.15.1 standard compatible) may be used to transferinformation between the telematics device 102 and the mobile device 110.In other embodiments, WPANs compatible with the IEEE 802 family ofstandards may be used. In one embodiment, the data radio 209 may be aBluetooth™ serial port adapter that communicates wirelessly via WPAN toa Bluetooth™ chipset located in the mobile device 110, or otherperipheral device. In addition, a Media Access Control (MAC) address,which is a code unique to each Bluetooth™-enabled device that identifiesthe device, similar to an Internet protocol address identifying acomputer in communication with the Internet, can be communicated toother devices in communication with the WPAN, which may assist inidentifying and allowing communication among vehicles, cargo, and mobiledevices equipped with Bluetooth™ devices. As discussed above with regardto FIG. 2, and as one of ordinary skill in the art will readilyrecognize, other wireless protocols exist (e.g., cellular technology)and can likewise be used in association with embodiments of the presentinvention.

As described in greater detail below, in various embodiments, thetelematics device 102 may be configured to capture and store telematicsdata from the vehicle sensors 410 at predefined time intervals and inresponse to detecting the occurrence of one or more of a plurality ofpredefined vehicle events. Generally, a vehicle event may be defined asa condition relating to any parameter or combination of parametersmeasurable by the one or more vehicle sensors 410 (e.g., the engineidling, vehicle speed exceeding a certain threshold, etc.). As such, thetelematics device 102 may be configured to continuously monitor thevarious vehicle sensors 410 and detect when the data being generated byone or more the vehicle sensors 410 indicates one or more of theplurality of predefined vehicle events. In response to detecting avehicle event, the telematics device 102 captures data from all of thevehicle sensors 410 or a particular subset of the vehicle sensors 410associated with the detected vehicle event.

As an example, the telematics device 102 may be configured to recognizethe occurrence of a first vehicle event (e.g., the vehicle's 100 enginebeing turned on or off), a second vehicle event (e.g., the vehicle's 100speed exceeding a certain threshold), and a third vehicle event (e.g., aseat belt in the vehicle 100 being engaged or disengaged). In oneembodiment, the telematics device 102 is configured to capture and storetelematics data from all of the vehicle sensors 410 in response todetecting any of the first vehicle event, the second vehicle event, andthe third vehicle event. In another embodiment, the telematics device102 is further configured such that the first vehicle event isassociated with a first subset of vehicle sensors (e.g., the seat beltsensor and location sensor), the second vehicle event is associated witha second subset of vehicle sensors (e.g., a vehicle speed sensor andlocation sensor), and the third vehicle event is associated with a thirdsubset of vehicle sensors (e.g., a seat belt sensor, engine speedsensor, and vehicle speed sensor). Accordingly, in this embodiment, thetelematics device 102 will capture and store telematics data from thefirst set of vehicle sensors after detecting the first vehicle event,the second set of vehicle sensors after detecting the second vehicleevent, and the third set of vehicle sensors after detecting the thirdvehicle event.

The vehicle events programmed for recognition by the telematics device102 can be defined in a variety of ways. As will be appreciated from thedescription herein, the telematics device 102 may be configured tocapture telematics data in response to vehicle events defined by anycombination of conditions sensed by the vehicle sensors 410. Thesepredefined vehicle events may be stored, for example, on the telematicsdevice's memory modules 210, or on another data storage mediumaccessible by the telematics device's processor 201.

For example, in various embodiments, the telematics device 102 isconfigured to recognize vehicle events characterized by data generatedby on/off vehicle sensors. These vehicle events may include: (a) avehicle's engine being turned on, (b) a vehicle's engine being turnedoff, (c) a vehicle door opening, (d) a vehicle door closing, (e) avehicle door being locked, (f) a vehicle door being unlocked, (g) avehicle's reverse gear being selected, (h) a vehicle's one or moreforward drive gears being selected, (i) a vehicle's neutral or park gearbeing selected, (j) a vehicle's parking break being engaged, (k) avehicle's seat belt being engaged, (l) a vehicle's seat belt beingdisengaged, and any other event definable by a parameter measured by anon/off sensor.

In addition, various embodiments of the telematics device 102 are alsoconfigured to recognize vehicle events characterized by data generatedby variable voltage vehicles sensors or other types of dynamic vehiclesensors. These vehicle events may include (a) a vehicle's speedincreasing from standstill to a non-zero value, (b) a vehicle's speeddecreasing from a non-zero value to standstill, (c) a vehicle's enginespeed exceeding a certain threshold, (d) a vehicle's engine speeddropping below a certain threshold, (e) a vehicle beginning to move in areverse direction, (f) a vehicle ceasing to move in a reverse direction,(g) a vehicle's heading reaching a threshold away from center, (h) avehicle's engine temperature exceeding a certain threshold, (i) avehicle's gas level falling below a certain level, (j) a vehicle's speedexceeding a certain threshold, and any other event definable by aparameter measured by a variable voltage or other dynamic sensor.

In addition, various embodiments of the telematics device 102 are alsoconfigured to recognize vehicle events characterized by data generatedby GPS-sensors or other location sensing devices. These vehicle eventsmay include (a) a vehicle moving into a geo-fenced area (e.g., ageo-fenced area defining a shipping hub, delivery area, or other workarea), (b) a vehicle moving out of a geo-fenced area (e.g., a geo-fencedarea defining a shipping hub, delivery area, or other work area), (c) avehicle traveling onto a predefined route (e.g., a GPS-based roadroute), (d) a vehicle traveling off of a predefined route, (e) a vehicletraveling onto a known road (e.g., a road recognized by a GPS device),(f) a vehicle traveling off of a known road (e.g., exceeding a certainpredefined distance from a known road), and any other event definable bya parameter measured by a location sensing device.

According to various embodiments, the telematics device 102 may be alsoconfigured to recognize multiple unique vehicle events based on a singlevarying parameter measured by one of the vehicle sensors 410. As oneexample, the telematics device 102 may be configured such that a firstvehicle event is detected anytime the vehicle's speed begins to exceed50 miles-per-hour, while a second vehicle event is detected anytime thevehicle's speed begins to exceed 70 miles-per-hour. As such, thetelematics device 102 may capture telematics data from vehicle sensors410 in response to the vehicle 100 accelerating past 50 miles-per-hour,and again as the vehicle 100 accelerates past 70 miles-per-hour. Inaddition, as noted earlier, the telematics device 102 may capturetelematics data from unique subsets of vehicle sensors based on thevarying measurements of vehicle speed (e.g., a first subset of vehiclessensors associated with the 50-mph vehicle event and a second subset ofvehicle sensors associated with the 70-mph vehicle event). This conceptmay also be applied to other variable parameters sensed by vehiclesensors, such as vehicle heading (e.g., various threshold degrees fromcenter), engine speed (e.g., various threshold RPM measurements), andvehicle distance from a predefined path (e.g., threshold value for feetfrom a known road, vehicle route, or other GPS-based geographiclocation).

In addition, vehicle events may be defined by a combination ofconditions indicated by various vehicle sensors 410. For example, incertain embodiments, the telematics device 102 may be configured todetect instances of stationary vehicle engine idling (e.g., where theengine is on and the vehicle is not moving) based on a combination ofdata from a vehicle engine sensor and a vehicle speed sensor. In suchembodiments, a first vehicle event is defined as the vehicle 100 beingturned on and beginning to idle (e.g., instances in which the vehiclesensors 410 indicate the vehicle's engine is turned on and the vehiclespeed is zero), a second vehicle event is defined as the vehicle 100beginning to move and thereby ceasing to idle (e.g., instances in whichthe vehicle sensors 410 indicate the vehicle's engine is on and thevehicle's speed has increased from zero to a non-zero value), a thirdvehicle event is defined as the vehicle 100 slowing to a stop andbeginning to idle again (e.g., any instance in which the vehicle sensors410 indicate the vehicle's engine is on and the vehicle's speed hasdecreased from a non-zero value to zero), and a fourth vehicle event isdefined as the vehicle 100 being turned off and again ceasing to idle(e.g., any instance in which the vehicle sensors 410 indicate thevehicle's engine is turned off and the vehicle speed is zero). As aresult, in this embodiment, vehicle events are detected and telematicsdata is captured at the beginning and end of every period during whichthe vehicle's engine is idling. In various embodiments, the telematicsdevice 102 captures every period of engine idling for each deliveryvehicle. Other examples of vehicle events defined by a combination ofconditions include (a) where a vehicle seat belt is engaged ordisengaged while the vehicle is idling, (b) where a vehicle exceeds acertain speed while located within a certain geographic area associatedwith the certain speed, and (c) a vehicle door opening or closing whilethe engine is on.

In addition to capturing telematics data in response to detected vehicleevents, the telematics device 102 may be further configured toautomatically capture telematics data from the vehicle sensors 410 atpredefined time intervals. For example, in one embodiment, thetelematics device 102 is programmed with a threshold data capture time(e.g., 10 seconds, one minute) and is configured to automaticallycapture telematics data from the vehicle sensors 410 where no vehicleevents are detected for a period exceeding the defined time. Thisconfiguration ensures that the threshold data capture time is thelongest possible duration between telematics data being collected andensures that the vehicle 100 is continuously monitored even throughperiods where none of the predefined vehicle events are detected. Aswill be appreciated from the description herein, the threshold datacapture time may be defined as any period of time according to thepreference of a fleet management system 5 user.

Although the telematics device 102 is described above as capturingtelematics data in response to detected vehicle events, or in responseto a certain elapsed time, the telematics device 102 may also beconfigured to capture telematics data in response to other occurrences.For example, the telematics device 102 may be triggered remotely fromthe central server 120 or mobile device 110 to capture telematics datafrom all, or particular, vehicle sensors at any time. For example, inone embodiment, a driver may use a particular button or enter aparticular command on the mobile device's 110 user interface in order totrigger the capture of telematics data by the telematics device 102. Inanother embodiment, the mobile device 110 may be configured to notifythe telematics device of particular delivery events in order to triggerthe telematics device 102 to capture of telematics data.

As noted above, in response to a triggering event—such as a definedvehicle event or elapsed threshold data capture time—the telematicsdevice 102 captures telematics data from the vehicle sensors 410. In oneembodiment, the telematics device 102 is configured to store thecaptured telematics data in fields of one or more data records, eachfield representing a unique measurement or other data from a uniquevehicle sensor. As the telematics device 102 continues to capturetelematics data in response to triggering events, multiple records ofdata comprising multiples sets of concurrently captured telematics dataare amassed. The captured telematics data may be initially stored, forexample, in the telematics devices memory modules 201, in another datastorage component of the telematics device 102, or in a remote location(e.g., a cloud database).

In one embodiment, the telematics device 102 may be configured tocontinuously or periodically store GPS readings and/or other telematicsdata (e.g., including position, time, and speed information/data),regardless of whether a trigger event has occurred. This may bebeneficial since GPS readings may not always be available at any givenmoment in time since the GPS signal could be temporarily blocked by anearby object or device or otherwise be unavailable (e.g., if thevehicle 100 is in a parking garage, is in covered parking area, iscovered by foliage from trees, etc.). In the event of a GPS signal loss,the telematics device 102 may store information about the time andlocation the GPS signal was lost. The telematics device 102 may alsostore information about the time and location the GPS signal wasregained/acquired.

In various embodiments, after capturing data from any of the vehiclesensors 410, the telematics device 102 may be further configured toconcurrently capture and store contextual data. The contextual data mayinclude, for example, the date (e.g., 12/30/10) and time (e.g., 13:24)the data was captured, the vehicle from which the data was captured(e.g., a vehicle identification number such as 16234), the driver of thevehicle from which the data was captured at the time it was captured(e.g., John Q. Doe), and/or a logged reason for the data capture (e.g.,a code indicating a detected vehicle event or indicating that thepredefined time interval had elapsed). The contextual data may becaptured, for example, from various telematics device components (e.g.,an internal clock) and from data stored on the telematics device 102(e.g., current driver name, current vehicle id, or various vehicle eventcodes). Further, the telematics device 102 may be configured toassociate the captured telematics data with the captured contextual datain order to ensure concurrently captured telematics data and contextualdata are linked. For example, in one embodiment, the telematics device102 stores concurrently captured telematics data and contextual data inthe same data record or records.

In various embodiments, a driver may be required to enter his or herdriver ID number (or name) and vehicle id number at the beginning ofeach day (e.g., using the mobile device 110 in communication with thetelematics device 102) in order to enable the telematics device 102 toassociate telematics data captured that day with accurate contextualdata. In other embodiments, the telematics device 102 may be programmedremotely (e.g., from the central server 120 over the network 130) suchthat it is associated with the appropriate driver and vehicleinformation. According to various embodiments, the contextual data maybe formatted in any computer-readable and transmittable data format. Forexample, in one embodiment, the contextual data is metadata. As thetelematics data captured from the various vehicle sensors 410 isassociated with the captured contextual data, the central server 120will later be able to associate the telematics data with correspondingservice data (e.g., based on time, driver, and/or vehicle), as well assearch and identify stored telematics data based on—for example—aparticular date, time, vehicle, driver, and/or vehicle event.

As noted above, the telematics device 102 is also configured to transmitcaptured telematics data and contextual data to the mobile device 110and/or the central server 120. According to various embodiments, thecaptured data may be transmitted using any of the communication methodsor protocols described herein, as well as various other methods andprotocols known in the art. For example, the telematics device 102 maybe configured to first attempt to establish a connection with thecentral server 120 (e.g., via a wireless signal). If a successfulconnection is made, the telematics device 102 will transfer captureddata to the central server 120. However, if a successful connectioncannot be made, the telematics device may be configured to alternativelytransfer data to the mobile device 110 (e.g., via a wireless signal orUSB connection). In other embodiments, the telematics device 102 may beconfigured to always transfer data to the mobile device 110, even wherethe data is also transmitted to the central server 120.

According to various embodiments, the defined vehicle events thattrigger the telematics device 102 to capture and store telematics data,the sensors 410 from which telematics data are captured, and theintervals defined for capturing and storing data when no vehicle eventsare detected each may impact the effectiveness with which the fleetmanagement system 5 is able to evaluate the captured telematics data.For example, capturing data from a large number of vehicle sensors at ahigh frequency may allow the fleet management system 5 to analyze thetelematics data with greater accuracy. This could be accomplished, forexample, by a fleet management system with many defined vehicle eventsand relatively short intervals for automatically capturing telematicsdata.

However, as some embodiments of the fleet management system 5 will havemore limited storage capacity for storing captured telematics data, theamount of telematics data collected may be regulated based on the systemvariables described above. For example, a system user that has limiteddata storage resources and that is particularly interested in monitoringseat belt usage in a fleet of vehicles may configure the telematicsdevices 102 of the fleet vehicles 100 to capture and store data fromonly those sensors relevant to seat belt status. In addition, the usermay configure the telematics devices 102 to capture data at the minimalfrequency necessary to accurately report seat belt usage. Thisembodiment could use, for example, a small number of vehicle events andlong time interval for capturing telematics data when no vehicle eventsare detected. As a contrasting example, a large fleet management entityhaving large amounts of data storage resources may configure thetelematics devices 102 of its large fleet of vehicles 100 to capture andstore data from a wide variety of vehicle sensors at a high frequencysuch that the telematics data may be analyzed to assess a wide varietyof vehicle and driver efficiencies. As described above, this embodimentcould use, for example, a large number of vehicle events and short timeinterval for automatically capturing telematics data. Accordingly, thetelematics device 102 may be flexibly configured to suit the needs of aparticular fleet management system 5 user.

Mobile Device

As noted above, the mobile device 110 may be configured for receivingand storing user input received from a driver, receiving and displayinginformation received from the central server 120, receiving and storingtelematics data received from the telematics device 102, andtransmitting any received data to the central server 120 over thenetwork 130. According to various embodiments, the various functions ofthe mobile device 110 described herein may be generally understood asbeing performed by one or more of the mobile device 110 componentsdescribed below.

According to various embodiments, the mobile device 110 may be ahandheld electronic device capable of data acquisition, such as adelivery information acquisition device (DIAD), pocket PC, personaldigital assistant (PDA), handheld computer, smartphone, laptop,converged device, personal navigation device, computer, computingentity, mobile phone, tablet, notebook, laptop, watch, glasses, key fob,ear piece, camera, wristband, input terminal, processing device,processing entity, the like, and/or any combination of devices orentities adapted to perform the functions, operations, and/or processesdescribed herein—including both wireless and wireline devices. FIG. 4illustrates a schematic block diagram of a mobile device 110 accordingto one embodiment. In the illustrated embodiment, the mobile device 110includes an antenna 312, a transmitter 304, a receiver 306, and aprocessing device 308 (e.g., one or more processors, controllers, or thelike) for providing signals to and receiving signals from thetransmitter 304 and receiver 306, respectively. As discussed in greaterdetail below, the processing device 308 may be configured to control thevarious functionalities of the mobile device 110, including receiving,storing, displaying, and transmitting operational data to and from thevarious components of the fleet management system 5. Although not shown,the mobile device 110 may also include a battery, such as a vibratingbattery pack, for powering the various circuits that are required tooperate the mobile device 110, as well as optionally providingmechanical vibration as a detectable output.

The signals provided to and received from the transmitter 304 and thereceiver 306, respectively, may include signaling information inaccordance with an air interface standard of applicable wirelesssystems. In this regard, the mobile device 110 may be capable ofoperating with one or more air interface standards, communicationprotocols, modulation types, and access types. More particularly, themobile device 110 may operate in accordance with any of a number ofsecond-generation (2G) communication protocols, third-generation (3G)communication protocols, and/or the like. Further, for example, themobile device 110 may operate in accordance with any of a number ofdifferent wireless networking techniques, including Bluetooth, IEEE802.11 (Wi-Fi), 802.16 (WiMAX), ultra wideband (UWB), and/or the like.Via these communication standards and protocols, the mobile device 110can communicate with the central server 120 and telematics device 102.The mobile device can also download changes, add-ons, and updates, forinstance, to its firmware, software (e.g., including modules), andoperating system.

The mobile device 110 can also include volatile memory 322 and/ornon-volatile memory 324, which can be embedded and/or may be removable.For example, the non-volatile memory 324 may be embedded or removablemultimedia memory cards (MMCs), secure digital (SD) memory cards, MemorySticks, EEPROM, flash memory, hard disk, or the like. The memory 322,324 can store any of a number of pieces or amount of information anddata used by the mobile device 110 to implement the functions of themobile device 110. For example, the volatile 322 and non-volatile 324memory can be used to temporarily or permanently store input fromexternal devices and/or input entered by the user via a user interface.The memory 322, 324 can also store content, such as computer programcode for an application and/or other computer programs. For example, thememory 322, 324 may store computer program code for instructing theprocessing device 308 to perform operations discussed above and below.

In various embodiments, the mobile device 110 may also include alocation sensing device (e.g., a Global Positioning System (GPS) deviceor other location sensor, such as those described above in relation tothe telematics device 102) for providing location information in theform of, for example, latitude and longitude values. In particularembodiments, this location sensing device may be used to gatherinformation regarding the location of the driver him- or herself, asopposed to location information associated with the delivery vehicle100, which is collected (or determined) by the telematics device 102 incertain embodiments.

According to various embodiments, the mobile device 110 further includesa user interface comprising a display 316, which may be coupled to theprocessing device 308, and one or more input devices allowing the mobiledevice 110 to receive data, such as a keypad 318, touch display (notshown), barcode reader (not shown), RFID tag reader (not shown), and/orother input devices. In embodiments including a keypad 318, the keypad318 may include conventional numeric (e.g., 0-9) and related keys (e.g.,#, *), a full set of alphabetic keys or set of keys that may beactivated to provide a full set of alphanumeric keys, speciallyprogrammed keys to activate selected functions, and other keys used foroperating the mobile device 110. In addition to receiving input, theuser interface can be used, for example, to activate or deactivatecertain functions, such as screen savers and/or sleep modes.

According to various embodiments, the mobile device 110 is configuredfor receiving user input (e.g., via the user interface) and storing thereceived user input as service data. In particular, a vehicle operator(e.g., driver) may indicate a variety of service dynamics, such asdelivery- or vehicle-related activities or occurrences, by using theuser interface's keypad 318 and other input devices. For example, invarious embodiments, the user interface is configured to permit a driverto indicate the following service dynamics: (a) that a delivery stop hascommenced (e.g., by pressing a button indicating that the driver hasarrived at a delivery location and commenced the delivery process), (b)that a delivery stop has ended (e.g., by pressing a button indicatingthat the driver has completed the delivery and is now leaving thedelivery location), (c) that a particular bill of lading and itsassociated freight or packages have been picked up or delivered (e.g.,by entering or scanning a tracking number or code, or otherwiseidentifying one or more bills of lading associated with freight orpackages that have been picked up or delivered), (d) the number of unitspicked up or delivered at a stop (e.g., by manually entering a numericalvalue), (e) the weight of packages or freight picked up or delivered ata stop (e.g., by manually entering a numerical value), (f) that a lunchor break period has commenced or ended (e.g., by pressing a buttonindicating that the start or stop of a break or lunch), (g) that aparticular delay encountered by a driver has commenced or ended (e.g.,by entering a code or otherwise identifying a type of delay that adriver has encountered—such as waiting for freight, caught in traffic,fueling a vehicle, waiting at train tracks, waiting at security, waitingfor bill of lading—and pressing a button indicating that the identifieddelay has started or stopped), (h) that the driver has begun a work dayand is on the clock (e.g., at a shipping hub and before starting thevehicle 100), (i) that the driver has ended a work day and is off theclock, (j) that the driver and vehicle have entered a particular area(e.g., the property of a shipping hub, a designated delivery area orother work area), and (k) that the driver and vehicle have exited aparticular area (e.g., the property of a shipping hub, a designateddelivery area or other work area).

In response to receiving user input indicating any of these occurrences,the mobile device 110 may capture and store the received input asservice data in a computer readable format. In accordance with thevarious features of the user interface, the stored service data may takea variety of forms. For example, user input in the form of manuallyentered alphanumeric text may be stored as a copy of the entered text(e.g., a manually entered tracking number, reason for a delay, locationof delay, etc.). In contrast, user input in the form of a user selectionof a user interface button or touchpad option (e.g., a selectionindicating a stop has commenced) may be recognized by the mobile device110 and stored as data representing the indicated occurrence. Forexample, if a user selects a button indicating that an unplanned delaydue to traffic has begun, the mobile device 110 may store the input as acode corresponding to the commencement of the indicated delay (e.g.,B-TR01) or as text indicating the commencement of the indicated delay(e.g., Start Traffic Delay).

After receiving input via the user interface and capturing the input asservice data, the mobile device 110 may be further configured toconcurrently capture and store contextual data. The contextual data mayinclude, for example, the date (e.g., 12/30/10) and time (e.g., 13:24)the service data is captured, the driver associated with the mobiledevice 110 at the time the service data is captured (e.g., John Q. Doe),the vehicle with which that driver is associated at the time the servicedata is captured (e.g., a vehicle identification number such as 16234),the location of the mobile device 110 at the time the service data iscaptured (e.g., GPS coordinates), the type of service data captured(e.g., delay code, stop status), and—where applicable—the stop number atwhich the service data is captured (e.g., stop 3). The contextual datamay be captured, for example, from various mobile device 110 components(e.g., an internal clock, location sensing device) and from data storedon the mobile device 110 (e.g., current driver name, current vehicleid). Further, the mobile device 110 is configured to associate thecaptured service data with the captured contextual data in order toensure concurrently captured service data and contextual data capturedare linked. For example, in one embodiment, the mobile device 110 storesconcurrently captured service data and contextual data in the same datarecord or records. As the service data captured by the mobile device 110is associated with captured contextual data, the central server 120 willlater be able to associate the service data with correspondingtelematics data (e.g., based on time, driver, and/or vehicle), as wellas search and identify stored service data based on—for example—aparticular data, time, vehicle, and/or driver.

As noted earlier in regard to the telematics device 102, in certainembodiments, a driver may be required to enter his or her driver IDnumber (or name) and vehicle ID number at the beginning of each day inorder to enable the mobile device 110 to associate captured service datawith contextual data. In other embodiments, the mobile device 110 may beprogrammed remotely (e.g., from the central server 120 over the network130) such that it is associated with the appropriate driver and vehicleinformation. According to various embodiments, the contextual data maybe formatted in any computer-readable and transmittable data format. Forexample, in one embodiment, the contextual data is metadata.

As noted earlier, the mobile device 110 may also be configured forstoring telematics data received from the telematics device 102, and fortransmitting such data to the central server 120 (e.g., where thetelematics device 102 is unable to establish a suitable connection withthe central server 120). After storing captured service data andcontextual data, and/or receiving telematics data, the mobile device 110is further configured to transmit the data to the central server 120.According to various embodiments, the captured data may be transmittedusing any of the communication methods or protocols described herein, aswell as various other methods and protocols known in the art.

In addition, the mobile device 110 may also store service data receivedfrom the central server 120, such as data indicating the weight, numberof units, or type of items comprising a driver's current shipment. Thisdata may later be associated with telematics data captured by thetelematics device 102 while that particular shipment is being delivered.The mobile device 110 is also configured for displaying (e.g., via thedisplay 316) data received from the central server 120 and telematicsdevice 102. For example, the mobile device 110 may receive and displaydelivery information from the central server 120 (e.g., updatedinstructions for a particular delivery) or telematics data from thetelematics device 102 (e.g., an alert that engine temperature is toohigh, tire pressure is too low, or recent gas mileage is poor).According to various embodiments, the mobile device 110 may communicatewith other components of the fleet management system 5 using theabove-described communication methods and protocols.

Central Server

As noted above, various embodiments of the central server 120 aregenerally configured for receiving and storing operational data (e.g.,telematics data received from the telematics device 102 and service datareceived from the mobile device 110) and evaluating the operational datafor a fleet of vehicles in order to assess various fleet efficienciesand aid fleet management system 5 users in improving the operationalefficiency of the fleet. In general, the term server and/or similarwords used herein interchangeably may refer to, for example, one or morecomputers, computing entities, computing devices, mobile phones,desktops, tablets, notebooks, laptops, distributed systems, servers,blades, gateways, switches, processing devices, processing entities,relays, routers, network access points, base stations, the like, and/orany combination of devices or entities adapted to perform the functions,operations, and/or processes described herein. According to variousembodiments, the central server 120 includes various means forperforming one or more functions in accordance with embodiments of thepresent invention, including those more particularly shown and describedherein. As will be appreciated from the description herein, however, thecentral server 120 may include alternative devices for performing one ormore like functions without departing from the spirit and scope of thepresent invention.

FIG. 5 illustrates a schematic diagram of the central server 120according to various embodiments. The central server 120 includes aprocessor 60 that communicates with other elements within the centralserver 120 via a system interface or bus 61. In the illustratedembodiment, the central server 120 includes a display device/inputdevice 64 for receiving and displaying data. This display device/inputdevice 64 may be, for example, a keyboard or pointing device that isused in combination with a monitor. In certain embodiments, the centralserver 120 may not include a display device/input device and may bealternatively accessed by a separate computing device (e.g., a networkedworkstation) having a display device and input device. The centralserver 120 further includes a power supply 68 and memory 66, whichpreferably includes both read only memory (ROM) 65 and random accessmemory (RAM) 67. The server's ROM 65 is used to store a basicinput/output system 26 (BIOS), containing the basic routines that helpto transfer information between elements within the central server 120.

In addition, the central server 120 includes at least one storage device63—such as a hard disk drive, a floppy disk drive, a CD Rom drive, oroptical disk drive—for storing information on various computer-readablemedia, such as a hard disk, a removable magnetic disk, or a CD-ROM disk.As will be appreciated by one of ordinary skill in the art, each ofthese storage devices 63 is connected to the system bus 61 by anappropriate interface. The storage devices 63 and their associatedcomputer-readable media provide nonvolatile storage for a personalcomputer. It is important to note that the computer-readable mediadescribed above could be replaced by any other type of computer-readablemedia known in the art. Such media include, for example, magneticcassettes, flash memory cards, digital video disks, and Bernoullicartridges.

A number of program modules may be stored by the various storage devicesand within RAM 67. Such program modules include an operating system 80,a plurality of program modules 1000-2300. According to variousembodiments, the modules 1000-2300 control certain aspects of theoperation of the central server 120 with the assistance of the processor60 and operating system 80. Embodiments of these modules are describedin more detail below in relation to FIGS. 10-39.

In a particular embodiment, these program modules 1000-2300, areexecuted by the central server 120 and are configured to generategraphical user interfaces accessible to users of the system. In oneembodiment, the user interfaces may be accessible via the Internet orother communications network. In other embodiments, one or more of themodules 1000-2300 may be stored locally on one or more computers andexecuted by one or more processors of the computers.

According to various embodiments, the central server 120 is configuredto send data to, receive data from, and utilize data contained in acentral server database, which may be comprised of one or more separate,linked databases. For example, in executing the various modules1000-2300, the central server 120 may retrieve data necessary forperforming various analyses from the central server database, and maystore data resulting from various analyses in the central serverdatabase. According to various embodiments, the central server databasemay be a component of the central server 120, or a separate componentlocated remotely from the central server 120. In addition, the centralserver database may be configured for storing data in various data sets.In various embodiments, each data set may comprise a plurality of storeddata records, each record (or set of associated records) comprising oneor more data fields of unique data entries. For example, telematics dataand contextual data concurrently captured by the telematics device 102may be stored in a data record, where each data field in the data recordrepresents a unique data entry (e.g., a measurement of vehicle speed,GPS coordinates, the time and date the data was captured, and an IDnumber of the vehicle from which the data was captured).

Also located within the central server 120 is a network interface 74,for interfacing and communicating with other elements of a computernetwork. It will be appreciated by one of ordinary skill in the art thatone or more of the central server 120 components may be locatedgeographically remotely from other central server 120 components.Furthermore, one or more of the components may be combined, andadditional components performing functions described herein may beincluded in the central server 120.

While the foregoing describes a single processor 60, as one of ordinaryskill in the art will recognize, the central server 120 may comprisemultiple processors operating in conjunction with one another to performthe functionality described herein. In addition to the memory 66, theprocessor 60 can also be connected to at least one interface or othermeans for displaying, transmitting and/or receiving data, content or thelike. In this regard, the interface(s) can include at least onecommunication interface or other means for transmitting and/or receivingdata, content or the like, as well as at least one user interface thatcan include a display and/or a user input interface. The user inputinterface, in turn, can comprise any of a number of devices allowing theentity to receive data from a user, such as a keypad, a touch display, ajoystick or other input device.

While reference is made to a central “server” 120, as one of ordinaryskill in the art will recognize, embodiments of the present inventionare not limited to a client-server architecture. The system ofembodiments of the present invention is further not limited to a singleserver, or similar network entity or mainframe computer system. Othersimilar architectures including one or more network entities operatingin conjunction with one another to provide the functionality describedherein may likewise be used without departing from the spirit and scopeof embodiments of the present invention. For example, a mesh network oftwo or more personal computers (PCs), or similar electronic devices,collaborating with one another to provide the functionality describedherein in association with the central server 120 may likewise be usedwithout departing from the spirit and scope of embodiments of thepresent invention.

Capturing Operational Data for a Fleet

According to various embodiments, the fleet management system 5 isconfigured to capture operational data from various delivery vehicles100 and their respective drivers over a period of time in order to amassdata reflecting the overall operations of the fleet. The operationaldata captured by the fleet management system 5 generally comprisesvehicle telematics data, which may be captured from various vehiclesensors by the telematics device 102, and service data, which may becaptured from driver input by the mobile device 110. Generally, thetelematics data is indicative of various vehicle dynamics (e.g., vehiclelocation, engine speed, etc.), while the service data is indicative ofdriver or delivery activity (e.g., driver status, status of variousdeliveries).

As described in greater detail below, the telematics device 102 andmobile device 110 are configured for capturing telematics data andservice data such that each type of data may later be evaluated in thecontext of the other. The captured operational data is then transmittedto the central server 120, which receives, processes, and stores thedata in order to it prepare it for evaluation in accordance with userrequests received via a graphical user interface.

Operation of Telematics Device Capturing Telematics Data

As noted above, according to various embodiments, the telematics device102 is generally configured to control various vehicle sensors 410positioned on a particular delivery vehicle 100, capture and storevehicle telematics data generated by those sensors 410, and transmit thetelematics data to the mobile device 110 and/or central server 120. FIG.6 illustrates exemplary steps executed by the telematics device 102 tocapture and transmit telematics data according to one embodiment. Invarious embodiments, the components of the telematics device 102described herein may be configured to execute the steps of FIG. 6 inaccordance with the principles described above.

Beginning with step 602, the telematics device 102 monitors datagenerated by the vehicle sensors 410 for parameters that matchpredefined vehicle events programmed in the telematics device 102. Inone embodiment, the telematics device 102 is programmed to monitor someor all the following predefined vehicle events in step 602: (a) thevehicle 100 being turned on and beginning to idle (e.g., where vehiclesensors 410 indicate the vehicle's engine is turned on and the vehiclespeed is zero), (b) the vehicle 100 beginning to move and therebyceasing to idle (e.g., where the vehicle sensors 410 indicate thevehicle's engine is on and the vehicle's speed has increased from zeroto a non-zero value), (c) the vehicle 100 slowing to a stop andbeginning to idle (e.g., where the vehicle sensors 410 indicate thevehicle's engine is on and the vehicle's speed has decreased from anon-zero value to zero), (d) the vehicle 100 being turned off andceasing to idle (e.g., where the vehicle sensors 410 indicate thevehicle's engine is turned off and the vehicle speed is zero), (e) thevehicle 100 moving out of a geo-fenced area associated with its homeshipping hub (e.g., as indicated by a GPS sensor), (f) the vehicle 100moving into a geo-fenced area associated with its home shipping hub, (g)the vehicle 100 moving into a geo-fenced area associated with a deliveryarea assigned to vehicle 100 and its driver, (h) the vehicle 100 movingout of a geo-fenced area associated with a delivery area assigned tovehicle 100 and its driver, (i) the vehicle 100 beginning to move in areverse direction, (j) the vehicle 100 ceasing to move in a reversedirection, and (k) the vehicle's seat belt being engaged or disengagedwhile the vehicle's engine is on.

Next, at step 604, the telematics device 102 determines whether any ofthe aforementioned predefined vehicle events have occurred. If a vehicleevent is detected, the telematics device 102 moves to step 606, where itcaptures and stores telematics data from the vehicle sensors 410. Asnoted earlier, the telematics data captured from the sensors 410 willindicate measurements or data from each of the vehicle sensors 410. Thistelematics data may indicate, for example, engine ignition status (e.g.,on or off), engine speed (e.g., RPM), vehicle speed (e.g., miles perhour), vehicle location (e.g., latitude and longitude), current distancetraveled (e.g., current odometer reading), location status (e.g.,on-property, on-area), seat belt status (e.g., engaged or disengaged),and vehicle backing status (e.g., moving in reverse or not moving inreverse). In one embodiment, the telematics device 102 stores capturedtelematics data in its memory modules 210, in another data storagecomponent of the telematics device 102, or in an associated database(e.g., a cloud database).

If a vehicle event is not detected in step 604, the telematics device102 moves to step 608, where it determines whether a threshold datacapture time has elapsed. For example, in one embodiment, the thresholddata capture time is defined as 30 seconds. If the telematics device 102determines that the threshold data capture time has not elapsed, itreturns to step 602 to continue monitoring for vehicle events. However,if the telematics device 102 determines that the threshold data capturetime has elapsed (e.g., more than 30 seconds have passed since the lasttime data was captured from the vehicle sensors), the telematics device102 moves to step 606 and captures telematics data from all of thevehicle sensors 410 as described above.

Next, at step 612, the telematics device 102 captures contextual dataand associates the contextual data with the telematics data captured andstored in step 606. In various embodiments, step 612 may be executedconcurrently with the step 606. In one embodiment, the telematics device102 is configured to capture some or all of the following contextualdata in step 612: the date (e.g., 12/30/10) and time (e.g., 13:24) thedata was captured, the vehicle from which the data was captured (e.g., avehicle identification number such as 16234), the driver of the vehiclefrom which the data was captured at the time it was captured (e.g., JohnQ. Doe), and a logged reason for the data capture (e.g., a codeindicating the detected vehicle event or indicating that the thresholddata capture time interval elapsed). Further, in one embodiment, thetelematics device 102 is configured to associate the captured telematicsdata with the captured contextual data by storing fields of telematicsdata captured from the vehicles sensors 410 in the same record, orrecords, as concurrently captured contextual data, thereby associatingconcurrently captured data.

Next, at step 614, the telematics device 102 transmits the telematicsdata and associated contextual data captured and stored in steps 606 and612 to the central server 120 or mobile device 110. This may beaccomplished by using any of the transmission methods and systemsdescribed herein, as well as other methods, protocols, and systems knownin the art. As described earlier, in one embodiment the telematicsdevice 102 is configured to first attempt to transmit captured data tothe central server 120, and subsequently attempt to transfer data to themobile device 110 if a connection with the central server 120 isunavailable.

Operation of Mobile Device Capturing Service Data

According to various embodiments, the mobile device 110 is configuredfor receiving user input via its user interface, capturing and storinguser input as service data, receiving telematics data from thetelematics device 102, and transmitting the captured service data andreceived telematics data to the central server 120. FIG. 7 illustratesexemplary steps executed by the mobile device 110 to capture andtransmit service data and telematics data. As will be appreciated fromthe description herein, in various embodiments, the various componentsof the mobile device 110 may be configured to execute the steps of FIG.7 in accordance with the principles described above.

Beginning with step 702, the mobile device 110 monitors its userinterface for user input (e.g., from a driver) and its receiver 306 forinbound telematics data (e.g., from the telematics deliver 102). In oneembodiment, the mobile device 110 is configured to receive and recognizeuser input indicating some or all of the following: (a) that a deliverystop has commenced, (b) that a delivery stop has ended, (c) that aparticular delivery stop is a pickup, delivery, or both, (d) that aparticular bill of lading and its associated freight or packages havebeen picked up or delivered, (e) the number of units picked up ordelivered at a stop, (f) the weight of packages or freight picked up ordelivered at a stop, (g) that a lunch or break period has commenced, (h)that a lunch or break period has ended, (i) that a particular delay hasbeen encountered, (j) that a particular delay has ended, (k) that adriver has begun a work day and is on the clock, (l) that a driver hasended a work day and is off the clock, (m) that the vehicle 100 hasmoved out of a geo-fenced area associated with its home shipping hub(e.g., as indicated by a GPS sensor), (n) that the vehicle 100 has movedinto a geo-fenced area associated with its home shipping hub, (o) thatthe vehicle 100 has moved into a geo-fenced area associated with adelivery area assigned to vehicle 100 and its driver, and (p) that thevehicle 100 has moved out of a geo-fenced area associated with adelivery area assigned to vehicle 100 and its driver.

At step 704, the mobile device 110 determines whether user input hasbeen received. If no inbound user input is detected, the mobile device110 moves to step 710, which is described in detail below. If the mobiledevice 110 detects user input (e.g., being input via the userinterface), the device 110 moves to step 706, where it captures the userinput and stores the input as service data. As described earlier, thecaptured the service data may be stored—for example—as a copy ofmanually entered data or data generated by the mobile device 110representing an occurrence indicated by the user (e.g., via a userinterface touchpad or buttons). The captured service data may be stored,for example, in the device's volatile memory 322 and/or non-volatilememory 324 and in a computer readable format.

Next, at step 708, the mobile device 110 captures contextual data andassociates the contextual data with the service data captured and storedin step 606. In various embodiments, step 708 may be executedconcurrently with step 706. In one embodiment, the mobile device 110 isconfigured to capture some or all of the following contextual data instep 708: the date (e.g., 12/30/10) and time (e.g., 13:24) the servicedata is captured, the driver associated with the mobile device 110 atthe time the service data is captured (e.g., John Q. Doe), the vehicleassociated with the driver at the time the service data is captured(e.g., a vehicle identification number such as 16234), the type ofservice data captured (e.g., delay code, stop status), and—ifapplicable—a stop number associated with the input service data (e.g.,stop 3). Further, the mobile device 110 is configured to associate thecaptured telematics data with the captured contextual data in order toensure concurrently captured service data and contextual data arelinked. For example, in one embodiment, the mobile device 110 isconfigured to store one or more fields of service data captured from thevehicles sensors 410 in the same record, or records, as concurrentlycaptured contextual data, thereby associating concurrently captureddata.

Next, at step 710, the mobile device 110 determines whether telematicsdata has been received (e.g., from the telematics device 102). If mobiledevice 110 does not detect that telematics data has been received, itmoves to step 714. If the mobile device detects that telematics data hasbeen received, it moves to step 712, where it stores the receivedtelematics data. The received telematics data may be stored, forexample, in the device's volatile memory 322 and/or non-volatile memory324. As noted above, this may occur where the telematics device 102transmits captured telematics data to the mobile device 110 in instanceswhen it is unable to establish a suitable connection for transmittingdata to the central server 120.

Next, at step 714, the mobile device 110 transmits any service datacaptured and stored in step 706 and any telematics data stored in step712 to the central server 120. According to various embodiments, themobile device 110 may execute step 714 via any suitable communicationmethod or protocol, including—but not limited to—those described herein.

Operation of Central Server Processing Telematics & Service Data

According to various embodiments, the central server 120 is configuredfor receiving, processing, and storing telematics data and service datareceived from the telematics device 102 and mobile device 110. Inparticular, the central server 120 processes and stores receivedtelematics data and service data in a manner that facilitates laterevaluation of both types of data in the context of one another.

According to various embodiments, in response to receiving inboundtelematics data or service data, the central server 120 is configured toprocess and store the data in an Operational Data Set stored on thecentral server database (which may comprise one or more separate, linkeddatabases, and may be a local or remote database). The central server120 populates the Operational Data Set by storing telematics data andservice data in association with concurrently captured contextual data,thereby providing a contextual relationship between all of the storedoperational data. For example, in various embodiments, the OperationalData Set comprises a plurality of data records representing concurrentlycaptured data. Each data record (or plurality of associated datarecords) comprises a plurality of data fields representing a unique dataentry.

In one embodiment, a data record of telematics data may comprise aplurality of data fields each representing a measurement from thevehicle sensors 410 (e.g., vehicle speed, vehicle location, enginespeed, seat belt status) and a plurality of data fields eachrepresenting a contextual data measurement (e.g., date, time, driver,vehicle, logged reason for data capture). The data in each data field ofthe record represents data captured concurrently with the data in theother data fields. Likewise, in one embodiment, a data record of servicedata may comprise a data field representing an indication received froma user (e.g., a delivery stop is being commenced) and a plurality ofdata fields each representing a contextual data measurement (e.g., date,time, driver, vehicle, stop number, bill of lading number). By storingtelematics data and service data in association with contextual data,the central server 120 may later access and retrieve data from theOperational Data Set by searching the stored data according to date,time, driver, vehicle, logged reason for data capture, or any other datafield or combination of data fields associated with the storedtelematics and service data (e.g., engine speed, vehicle speed, RPM,stop commenced, stop completed, lunch break commenced, lunch breakended, etc.).

In addition, according to various embodiments, the central server 120 isconfigured for maintaining a Planning Data Set stored in the centralserver database (or in another database accessible by the central server120). The Planning Data set may include stored data indicating, forexample, planned delivery routes for various drivers and vehicles (e.g.,a GPS-based route plan for a particular delivery vehicle 100), thelocations of planned stops along each delivery route (e.g., locationname and/or GPS location), planned distances associated with planneddelivery routes and stops (e.g., total planned distance for a deliveryroute, planned distances between planned stops), planned timesassociated various routes and stops (e.g., planned times for travelbetween stops, planned times for executing a delivery at a particularstop), planned delivery activities at each stop (e.g., pickup, delivery,pickup & delivery), particular packages or freight to be picked-up ordelivered at a given stop (e.g., one or more tracking numbers forpackages or freight), bills of lading associated with packages orfreight being picked up or delivered at a particular stop (e.g., anumber or code associated with a bill of lading), the weight of packagesor freight to be picked-up or delivered at a particular stop (e.g.,total weight for a pickup or delivery, or weight associated with aparticular bill of lading, package, or portion of freight), and thenumber of units to be picked up or delivered at each stop (e.g., totalnumber of units for a pickup or delivery, or number of units associatedwith a particular bill of lading).

The data stored in the Planning Data Set may be stored such that isassociated with, for example, a particular driver, delivery vehicle,route, date, and/or hub location. As such, the central server 120 mayaccess and retrieve data form the Planning Data Set by searching thestored data according to driver, vehicle, route, date, hub location, orany data field associated with the above described data (e.g., time,distance, weight, bill of lading number, tracking number, etc.).Accordingly, as described in greater detail below, the central server120 may retrieve planning data stored in the Planning Data Set for usein evaluating the operational data stored in the Operational Data Set.

Central Server User Interface

As described above, the central server 120 is configured for evaluatingoperational data (e.g., telematics data and service data) for a fleet ofvehicles in order to assess various fleet efficiencies and aid fleetmanagement system 5 users in improving the operational efficiency of thefleet. According to various embodiments, the central server's 120evaluation of operational data is conducted in accordance with userinstructions received via the central server's user interface. Invarious embodiments, the user interface is a graphical user interfaceaccessible from a remote workstation (e.g., in communication with thecentral server 120 via the network 130), or by using the centralserver's display device/input device 64.

For example, in various embodiments, a user may log in to the fleetmanagement system 5 from a remote workstation (e.g., by opening a log-inpage and entering a user id and password using a workstation display andkeyboard). The central server 120 may be configured to recognize anysuch log-in request, verify that user has permission to access thesystem (e.g., by confirming the user id and password are valid), andpresent the user with a graphical user interface (e.g., displayed on theworkstation's monitor). For example, FIG. 8 illustrates a start-up view800 of a central server graphical user interface according to oneembodiment. In the illustrated embodiment, the user interface 800includes a location pull-down menu 802, a pull-down date menu 804, adriver menu 806 sorted according to driver sorting options 808, a dataloading button 809, a map display 810, an evaluation results displayarea 820 configured for displaying various tables and analysis results,and a set of evaluation option tabs 825 displayed in association witheither an employee evaluation tab group 830 or a location evaluation tabgroup 840.

According to various embodiments, the menus 802-808 allow a system userto select certain operational data for evaluation by the central server120. For example, in one embodiment, the user may request evaluation ofoperational data for a particular driver (or drivers) by selecting oneor more drivers from the driver menu 806. Likewise, as the driver menu806 includes vehicle id numbers, the user may request evaluation ofoperational data for a particular vehicle. Further, the user may requestevaluation only of operational data captured for that driver (ordrivers) on a particular date or range of dates by also selecting adesired date or date range using the date menu 804. As additionalexamples, the user also has the option of requesting evaluation ofoperational data for all drivers based at a particular location (e.g.,by selecting only one or more shipping hub locations from the locationmenu 802), or for all drivers at all locations on a particular date(e.g., by selecting only a date or date range from the date menu 804).As will be appreciated from the description above, the user may requestevaluation of all operational data or any subset of operational datadefined by any combination of parameters provided in the menus 802-808.

After selecting operational data to be evaluated, the user may selectthe data loading button 809, which prompts the central server 120 toretrieve and segment the selected operational data. As discussed ingreater detail below, the central server's 120 segmentation of theoperational data enables the data to be assessed based on a variety ofefficiency criteria and metrics. As noted earlier, the user interface800 presents the user with an evaluation tab set 825 comprising aplurality of tabs associated with an employee evaluation tab group 830or a location evaluation tab group 840. By selecting the various tabs inthe evaluation tab set 825, the user may request various analyses of theselected operational data, the results of which are shown in theevaluation results display area 820 and map display 810.

According to various embodiments, the central server 120 is configuredto detect a user's selection of the various parameters and optionspresented on the user interface 800 and call one or more of the softwaremodules 1000-2300 in order to perform the appropriate data evaluation.FIG. 9 illustrates exemplary steps executed by the central server 120 inorder to respond to user evaluation requests received via the userinterface 800. Beginning at step 902, the central server 120 monitorsthe user interface 800 for user input (e.g., the selection of one of thetabs in the evaluation tab set 825, selection of the loading button 809,or another menu option). Next, at step 904, the central server 120determines whether the user has requested to load certain operationaldata (e.g., by selecting the data loading button 809, or buttonsprovided on the dispatch profile menu 2356 of FIG. 39). If the user hasnot requested data loading, the central server 120 moves to step 914,which is described in detail below. If the user has requested dataloading, the central server 120 moves to step 906.

At step 906, the central server 120 first identifies the operationaldata the user has selected for loading by reviewing the user's menuselections 802-808. For example, the user may request operational datarelating to a particular driver (e.g., by using the driver menu 806) andcaptured on a particular day (e.g., by using the date menu 804). Asanother example, the user may request operational data for all driversbased at a particular location and captured on a particular day or rangeof days (e.g., by selecting a location using the location menu 802 and adate or date range using the date menu 804, and not selecting aparticular driver). The central server 120 then accesses the operationaldata stored the Operational Data Set of the central server database,identifies and retrieves all operational data matching the user'sselections, and loads the retrieved data (e.g., in the central server'smemory) for use in performing analyses. In particular, as described ingreater detail herein, the user-selected operational data loaded by thecentral server 120 is used by the various modules 1000-2300 inperforming and presenting analyses of the user-selected data.

Next, at step 908, the central server 120 plots the vehicle's 100 travelpath on the map display 810 based on the operational data loaded in step906. In one embodiment, the central server 120 executes step 908 byfirst loading and displaying a base electronically navigable map (hereinthe “base map). For example, in various embodiments, the data comprisingthe base map may be stored on, and retrieved from, the central serverdatabase. Next, the central server 120 reviews the loaded operationaldata and identifies location data (e.g., captured GPS coordinates) andtime data (e.g., captured times, such as 09:38:12) associated with eachdata record in the loaded operational data. The central server 120 thengenerates a graphical representation of the vehicle's 100 travel path onthe map display 810. In one embodiment, the central server 120accomplishes this by plotting each individual location data point in theloaded operational data on the map display and then connecting theplotted location points in chronological order—based on the retrievedtime data—with lines displayed over the base map. In various embodimentsthe travel path generated by the central server 120 may comprise acolored line having a thickness greater than that of roads shown in thebase map and which includes arrows disposed along the travel path toindicate the direction of the vehicle's 100 travel. For example, FIG.13—which is discussed in greater detail below—shows a vehicle travelpath 1258 according to one embodiment. As noted earlier, the telematicsdevice 102 is configured to capture location data representing thegeographical position of the vehicle 100 when telematics data iscaptured from the vehicle (e.g., when a vehicle event is detected or thethreshold data capture time has elapsed). As such, the location datapresent in the loaded operational data is generally sufficient to enablethe central server 120 to accurately plot the path of the vehicle 100between the plotted stops.

Next, at step 910, the central server 120 calls the data segmentationmodule 1000, which—as described in greater detail below—evaluates theoperational data loaded in step 906 to identify and store variousvehicle- and delivery-related activity segments. In certain embodiments,the resulting segmented data is stored in a Segmented Data Set of thecentral server database. When the data segmentation module 1000 hascompleted segmenting the loaded operational data, the central server 120moves to step 912, where it retrieves and loads the segmented datacorresponding to the user-selected operational data for use in variousanalyses (e.g., by retrieving the data from the Segmented Data Set inthe central server database and loading it in the central server'smemory). As with the user-selected operational data, the segmented dataloaded by the central server 120 is used by the various modules1000-2300 in performing and presenting analyses of the user-selecteddata.

Next, at step 914, the central server 120 determines whether the userhas requested a particular evaluation of the selected data by selectingone of the tab groups 830, 840 and one of the tabs in an associated tabset 825. If the user has not requested data evaluation, the centralserver 120 moves back to step 902 and continues monitoring for userinput. If the user has selected a tab from the tab set 825, the centralserver moves to step 918 where it determines whether the appropriateuser-selected operational data has been loaded and segmented. If theuser-selected operational data has not been loaded and segmented, thecentral server 120 moves back to step 906—where it loads the selectedoperational data—and then loops back through steps 910-914. For example,where a user has loaded only operational data for a particular employee,but has selected a location-wide evaluation (e.g., an evaluationassociated with a tab in the location evaluation tab group 840), thecentral server 120 will loop back to step 906 and load the appropriateoperational data for all employees associated with the user's selectedlocation. Likewise, where a user has loaded operational data for allemployees at a particular location, but has selected anemployee-specific evaluation (e.g., an evaluation associated with a tabin the employee evaluation tab group 830), the central server 120 willprompt the user to select a particular employee and loop back to step906 to load the appropriate operational data. As a result, the centralserver 120 loads and evaluates operational data relevant to the user'srequested evaluation. If the appropriate user-selected operational datahas been loaded and segmented, the central server moves to step 920.

Finally, at step 920, the central server 120 calls the module associatedwith the evaluation option selected by the user. As described in greaterdetail below, the various modules 1000-2300 are each associated with aparticular tab in the evaluation tab set 825, which the user may selectto request a particular analysis of the selected operational data.

Data Segmenting Module

According to various embodiments, the data segmenting module 1000 isconfigured for evaluating operational data in order to identify segmentsof activity indicated by the data (herein referred to as “segmenting”the data). Each identified activity segment represents a period of time(e.g., 11:00 to 11:42 on 12/31/10) classified according to activity(e.g., vehicle stop time, vehicle travel time, driver lunch break). Inmany instances, certain activity segments may overlap with otheractivity segments (e.g., segments indicating engine idle timeattributable to a traffic jam may overlap with segments indicatingvehicle travel time). By segmenting the operational data captured by thetelematics device 102 and mobile device 110, the data segmenting module1000 can generate an accounting of activities occurring during thefleet's operating hours. As described in relation to the modules1000-2300 below, segmenting the captured operational data for a fleetenables the central server 120 to perform a variety of analyses in orderto assess various fleet efficiencies and to provide a graphicalrepresentation of vehicle and delivery activities for any period oftime.

In various embodiments, the data segmenting module 1000 is configured toidentify a plurality of programmed activity segments indicating variousvehicle-related, delivery-related, and/or driver-related activities andoccurrences. The data segmenting module 1000 identifies these activitysegments based on operational data stored in the Operational Data Set,which may include telematics data captured from the telematics device102 and service data captured from the mobile device 110. As discussedabove in regard to FIGS. 8 and 9, the central server 120 may call thedata segmenting module 1000 to segment operational data selected by auser using the user interface menus 802-808 (e.g., in step 906 of FIG.9). FIG. 10 illustrates steps executed by the data segmenting module1000 to segment user-selected operational data according to oneembodiment.

Beginning at step 1004, the data segmenting module 1000 first identifiesand stores all vehicle engine idle time segments indicated by theoperational data loaded by the central server 120 (e.g., the operationaldata loaded in step 906 of FIG. 9). According to various embodiments, anengine idle segment indicates a period of time during which thevehicle's engine is on and the vehicle's speed is zero. To identify suchengine idle segments, the data segmenting module 1000 first reviews theoperational data loaded by the central server 120 for data indicatingthe beginning or end of an engine idle segment. For example, in oneembodiment, the data segmenting module 1000 identifies the beginning ofengine idle segments by identifying, in the retrieved operational data,telematics data indicating instances where the vehicle's engine wasturned on (e.g., when the vehicle 100 is turned on and begins to idle)and instances where the vehicle's engine was on and the vehicle's speeddecreased from a non-zero value to zero (e.g., when the vehicle 100comes to a stop and begins idle). The data segmenting module 1000 thendefines the time at which each of the identified beginning instancesoccurred (e.g., as indicated by associated contextual data) as thebeginning of a unique engine idle segment. Likewise, in one embodiment,the data segmenting module 1000 identifies the end of engine idlesegments by identifying, in the retrieved operational data, telematicsdata indicating instances where the vehicle's engine was on and thevehicle speed increased from zero to a non-zero value (e.g., when thevehicle 100 begins moving and ceases to idle) and instances where thevehicle's engine was turned off (e.g., when the vehicle 100 is turnedoff and ceases to idle). The data segmenting module 1000 then definesthe time at which each of the ending instances occurred as the end of aunique engine idle segment.

In other embodiments, such engine idle segments can be determined usingother information from telematics data. For example, in one embodiment,the data segmenting module 1000 can analyze image data (e.g., capturedby the imaging devices) from the telematics data to determine when thevehicle 100 is stationary with its engine is on. This may be determined,for example, based on the vehicle's 100 position relative to otherobjects (e.g., signs) in the image data. In yet another example, thedata segmenting module 1000 may also identify engine idle segments basedon telematics data indicating that the vehicle's engine is on, but thatthe wheels are not rotating (e.g., based on hubometer readings). As willbe recognized, a variety of other approaches and techniques can be usedto adapt to various needs and circumstances.

Next, the data segmenting module 1000 links chronologically adjacentbeginning and ending instances to compose individual engine idlesegments each defined by a start time (e.g., 12:31:15) and end time(e.g., 12:32:29). The data segmenting module 1000 then stores theseengine idle segments in a Segmented Data Set in the central serverdatabase for use in further analyses. The resulting engine idle segmentsmay reflect segments of engine idle time attributable to a variety ofcontingencies, such as traffic during travel (e.g., idle segmentsbeginning where a vehicle's speed decreases to zero and ending where thevehicle's speed increases from zero) or driver activities in preparingto travel or preparing to stop (e.g., idle segments beginning with theengine being turned on or ending with the engine being turned off). Assuch, in one embodiment, the data segmenting module 1000 is configuredto store each engine idle segment in association with logged reasons fordata capture associated with the beginning and ending of a respectiveidle segment. The data segmenting module 1000 may accomplish this, forexample, by retrieving the logged reason for data capture from thecontextual data associated with the start of the engine idle segment(e.g., a code indicating the vehicle was turned on, a code indicatingthe vehicle slowed from speed to a stop) and the end of the engine idlesegment (e.g., a code indicating the vehicle was turned off, a codeindicating the vehicle has accelerated from standstill). In addition, inone embodiment, the engine idle segments—as well as the other identifiedsegments discussed herein—are stored in the Segmented Data Set inassociation with contextual data indicating the operational data fromwhich they were derived (e.g., data indicating the user-selected dateand driver corresponding to the operational data loaded in step 906 ofFIG. 9).

Next, at step 1006, the data segmenting module 1000 identifies andstores various vehicle trip segments based on the identified engine idlesegments. According to various embodiments, a vehicle trip generallyrepresents a vehicle's transit time from an origin location to adestination location (e.g., beginning when the vehicle's engine isturned on at the origin location and ending when the vehicle's engine isturned off at the destination location). In step 1006, the datasegmenting module 1000 identifies such vehicle trips and breaks eachvehicle trip into a Start of Trip segment, a Travel segment, and an Endof Trip segment. Generally, the Start of Trip segment begins with thevehicle's engine turning on at its origin location and ends when thevehicle 100 first begins to move, the Travel segment beings when thevehicle 100 beings to move and ends when the vehicle 100 stops at itsdestination location, and the End of Trip segment begins when thevehicle 100 stops at its destination location and ends when thevehicle's engine is turned off.

To identify the various vehicle trip segments, the data segmentingmodule 1000 first reviews the engine idle segments identified in step1004 and identifies engine idle segments beginning with vehicle's enginebeing turned on (e.g., by reviewing the contextual data indicating alogged reason for data capture associated with the beginning of eachstored engine idle segment, or by reviewing telematics data associatedwith the beginning of each stored engine idle segment). As these engineidle segments correspond to the Start of Trip segment of a vehicle trip,the data segmenting module 1000 then defines the identified idlesegments as Start of Trip segments in the Segmented Data Set. The datasegmenting module 1000 next reviews the engine idle segments identifiedin step 1004 and identifies engine idle segments ending with thevehicle's engine being turned off (e.g., by reviewing the associatedcontextual data indicating a logged reason for data capture associatedwith the ending of each stored engine idle segment, or by reviewingtelematics data associated with the ending of each stored engine idlesegment). As these engine idle segments correspond to the End of Tripsegment of a vehicle trip, the data segmenting module 1000 then definesthe identified idle segments as End of Trip segments in the SegmentedData Set. Finally, the data segmenting module 1000 reviews the Start ofTrip and End of Trip segments in the Segmented Data Set, identifies allperiods of time existing between the end of a Start of Trip segment andthe beginning of a corresponding End of Trip Segment (e.g., 9:45:16 to10:05:23), and stores each identified time period as a Travel segment inthe Segmented Data Set. Accordingly, in one embodiment, each storedStart of Trip segment, End of Trip segment, and Travel segment aredefined by data indicating the respective segment's start time (e.g.,10:18:23), end time (e.g., 10:26:12), and the segment type (e.g., Startof Trip, End of Trip, Travel).

Next, at step 1008, the data segmenting module 1000 identifies andstores Travel delay segments based on the previously identified engineidle segments and Travel segments. According to various embodiments, aTravel Delay segment represents a period of engine idle time occurringduring a Travel segment (e.g., when a vehicle is stopped at anintersection or stopped in heavy traffic). As such, to identify Traveldelay segments, the data segmenting module 1000 reviews all engine idlesegments identified in step 1004, identifies those engine idle segmentsoccurring during any Travel segment identified in step 1006 (e.g., bycomparing contextual data indicating the time each engine idle segmentbegins and ends with the time periods represented by each Travelsegment), and defines those engine idle segments as Travel delaysegments in the Segmented Data Set. Accordingly, in one embodiment, eachstored Travel Delay segment is defined by data indicating the segment'sstart time (e.g., 12:17:23), end time (e.g., 12:17:54), and the segmenttype (e.g., Travel Delay).

Next, at step 1010, the data segmenting module 1000 identifies andstores Stop segments indicated by the service data in the user-selectedoperational data loaded by the central server 120. According to variousembodiments, a Stop segment generally represents a period of time duringwhich a driver is performing a delivery (e.g., unloading freight ordelivering an individual package). As noted above, a driver may provideuser input to the mobile device 110 (e.g., via the user interface)indicating that a delivery stop has commenced or ended. As such, toidentify Stop segments, the data segmenting module 1000 reviews theoperational data loaded by the central server 120 and identifies servicedata indicating that a delivery stop has commenced or ended. The datasegmenting module 1000 then links chronologically adjacent delivery stopbeginning and ending instances to compose individual Stop segments eachdefined by a start time and end time. In addition, the data segmentingmodule 1000 determines whether the identified operational data indicatesa Stop type, such as whether the Stop is a delivery, pickup, or both.The data segmenting module 1000 then stores these Stop segments in theSegmented Data Set for use in further analyses. Accordingly, in oneembodiment, each stored Stop segment is defined by data indicating theStop's start time (e.g., 11:28:43), the Stop's end time (e.g.,11:38:12), and the Stop's type (e.g., delivery stop, pickup stop,delivery and pickup stop).

Next, at step 1012, the data segmenting module 1000 identifies andstores all Lunch, Break, and Coded Delay segments indicated by theservice data in the user-selected operational data loaded by the centralserver 120. According to various embodiments, Lunch and Break segmentsgenerally represent periods of time during which a driver has ceasedtraveling or delivery activity in order to eat lunch or take a break,while Coded Delay segments represent periods of time during which adriver has encountered an unexpected delay (e.g., due to traffic orvehicle trouble) and has indicated such a delay via the mobile device110. As noted above, a driver may provide user input to the mobiledevice 110 (e.g., via the user interface) indicating the beginning orend of a Lunch, Break, or Coded Delay segment. Accordingly, to identifyLunch, Break, and Coded Delay segments, the data segmenting module 1000reviews the service data present in operational data loaded by thecentral server 120 and identifies data indicating that a Lunch, Break,or Coded Delay has commenced or ended. The data segmenting module 1000then links chronologically adjacent Lunch beginning and endinginstances, and chronologically adjacent Break beginning and endinginstances, to compose individual Lunch and Break segments each definedby a start time and end time. Likewise, the data segmenting module 1000links chronologically adjacent Coded Delay beginning and endinginstances corresponding to the same delay type or delay code to composeindividual Coded Delay segments. The data segmenting module 1000 thenstores these Lunch, Break, and Coded Delay segments in the SegmentedData Set for use in further analyses. In one embodiment, each storedLunch, Break, or Coded Delay segment is defined by data indicating therespective segment's start time (e.g., 10:18:23), end time (e.g.,10:26:12), and segment type (e.g., lunch break, planned break, waitingfor freight coded delay, unexpected traffic coded delay, vehiclemaintenance coded delay).

Next, at step 1014, the data segmenting module 1000 identifies andstores On Property segments indicated by the user-selected operationaldata loaded by the central server 120. According to various embodiments,On Property segments generally represent periods of time when a vehicle100 is located on the property of its hub (e.g., a local shipping huboperated by a shipping entity) and the vehicle's driver is “on theclock” or otherwise working. As such, On Property segments mayrepresent—for example—periods of time during which a vehicle 100 anddriver are waiting to leave the hub at the beginning of a day (e.g.,waiting for delivery instructions, waiting for the vehicle 100 to befueled, or waiting for freight to be loaded), periods of time duringwhich a vehicle 100 and driver have returned to the shipping hub duringthe middle of a day (e.g., to retrieve additional packages or freight),and periods of time during which a vehicle 100 and driver have returnedto the shipping hub at the end of a day (e.g., navigating to thevehicle's parking space or waiting to complete documents).

As noted above, the telematics device 102 may be configured to detectwhen the vehicle 100 has entered or exited a particular geographic area,such as a geo-fenced area defining the shipping hub. Accordingly, in oneembodiment, the data segmenting module 1000 reviews the telematics datain the user-selected operational data loaded by the central server 120and identifies data indicating instances in which the vehicle 100 hasentered or departed the geographical area defining the shipping hub(e.g., by identifying contextual data indicating a logged reason fordata capture was the vehicle entering or departing the shipping hub areaand/or by identifying location-indicative telematics data anddetermining whether each indicated location is within the shipping hubarea). The identified data would include data indicating instances inwhich the vehicle's engine was turned on or turned off while within thegeo-fenced area. In addition, as noted earlier, a driver may manuallyindicate via the mobile device 110 when the vehicle has left a shippinghub property and when the vehicle has entered a shipping hub property.Furthermore, the mobile device 110 may also include a location sensor orother device configured to automatically determine when it has enteredor exited a geo-fenced area, such as a shipping hub property.Accordingly, in another embodiment, the data segmenting module 1000reviews the service data in the user-selected operational data loaded bythe central server 120 and identifies data indicating instances in whichthe vehicle 100 has entered or departed the geographical area definingthe shipping hub (e.g., in addition to, or in place of, reviewing thetelematics data to identify On Property segments).

In addition, as noted earlier, a driver may input service data to themobile device 110 indicating that the driver is beginning a work day atthe shipping hub and is on the clock (e.g., before starting the vehicle100) or that the driver has is ending a work day and is now off theclock. As such, the data segmenting module 1000 next reviews the servicedata in the user-selected operational data set loaded by the centralserver 120 for data indicating that a driver is at the shipping hub andis starting a work day, and for data indicating that a driver is at theshipping hub and ending a work day.

Next, the data segmenting module 1000 reviews the identified instancesnoted above and composes initial On Property segments (e.g., beginningwhen the driver's work day starts, as indicated by service data, andending when the vehicle first leaves the shipping hub area on aparticular day, as indicated by telematics data), intermediate OnProperty segments (e.g., beginning when a vehicle reenters the shippinghub area and ending when the vehicle next leaves the shipping hub areaas indicated by telematics data), and final On Property segments (e.g.,beginning when the vehicle last reenters the shipping hub area, asindicated by telematics data, and ending when the driver's work dayends, as indicated by service data). Each On Property segment may thenbe stored in the Segmented Data Set for use in further analyses. Foreach identified On Property segment, the data segmenting module 1000also reviews the telematics data in the loaded operational data toidentify instances in which the vehicle's engine was turned on or offduring a respective On Property segment. The data segmenting module 1000then stores these engine-on/engine-off instances as engine-status pointswithin the On Property segments in the Segmented Data Set. In oneembodiment, each stored On Property segment is defined by dataindicating the segment's start time (e.g., 08:15:43), end time (e.g.,08:45:12), segment type (e.g., On Property), and engine on/off instanceswithin the segment (e.g., E-On: 08:32:15, E-Off: 17:32:45).

As will be appreciated from the description herein, in otherembodiments, the data segmenting module 1000 may be configured toidentify On Property segments according to other definitions of thesegment. For example, in one embodiment, the data segmenting module 1000may be configured such that initial On Property segments begin when avehicle's engine is turned on while on the defined property (as opposedto when the driver's work day starts) and that final On Propertysegments end when the vehicle's engine is turned off while on thedefined property (as opposed to when the driver's work data ends).

Next, in step 1015, the data segmenting module 1000 identifies andstores On Area segments indicated by the user-selected operational dataloaded by the central server 120. According to various embodiments, OnArea segments generally represent periods of time when a vehicle 100 islocated within a predefined delivery and/or pickup area (herein“delivery area). A particular delivery area may comprise, for example,one or more residential neighborhoods and/or shopping areas and may bedefined, for example, as a geo-fenced area.

As noted earlier, the telematics device 102 may be configured to detectwhen the vehicle 100 has entered or exited a predefined geographic area,such as a geo-fenced, driver-assigned delivery area. Accordingly, in oneembodiment, the data segmenting module 1000 reviews the telematics datain the user-selected operational data loaded by the central server 120and identifies data indicating instances in which the vehicle 100 hasentered or departed a predefined delivery area (e.g., by identifyingcontextual data indicating a logged reason for data capture was thevehicle entering or departing a predefined delivery area and/or byidentifying location-indicative telematics data and determining whethereach indicated location is within a predefined delivery area). Inaddition, as noted earlier, a driver may manually indicate via themobile device 110 when the vehicle has entered or exited a predefineddelivery area. Accordingly, in another embodiment, the data segmentingmodule 1000 reviews the service data in the user-selected operationaldata loaded by the central server 120 and identifies data indicatinginstances in which the vehicle 100 has entered or exited thegeographical area defining the delivery area (e.g., in addition to, orin place of, reviewing the telematics data to identify On Areasegments).

Next, the data segmenting module 1000 reviews the identified instancesnoted above and composes On Area segments (e.g., beginning when thevehicle 100 enters a predefined delivery area and ending when thevehicle next exits the same predefined delivery area). The datasegmenting module 1000 then stores each composed On Area segment in theSegmented Data Set for use in further analyses. As will be appreciatedfrom the description herein, the data segmenting module 1000 may beconfigured to identify On Area segments associated with various uniquedelivery areas. Accordingly, in one embodiment, the data segmentingmodule 1000 is configured to store each identified On Area segment inassociation with contextual indicating the particular predefineddelivery area to which it corresponds.

Next, in step 1016, the data segmenting module 1000 identifies andstores Non-Travel Time to Stop segments indicated by the user-selectedoperational data loaded by the central server 120. According to variousembodiments, Non-Travel Time to Stop segments generally representperiods of time during which the vehicle 100 is not traveling and thedriver is not at a stop engaging in a delivery, on the property of theshipping hub, or in the midst of a lunch, break, or delay. In otherwords, Non-Travel Time to Stop segments occur where the driver isbetween stops, but is not traveling and has not otherwise accounted forhis or her time. To identify Non-Travel Time to Stop segments, the datasegmenting module 1000 reviews the previously identified Start of Tripsegments, Travel segments, End of Trip segments, On Property segments,Stop segments, Lunch segments, Break segments, and Delay segments, andidentifies periods of time within the operational data loaded by thecentral server 120 not accounted for by any of the aforementionedsegments. The data segmenting module 1000 then defines and stores theseidentified time periods as individual Non-Travel Time to Stop segmentsin the Segmented Data Set for use in further analyses. In oneembodiment, each stored Non-Travel Time to Stop segment is defined bydata indicating the segment's start time (e.g., 14:15:43), end time(e.g., 14:25:12), and segment type (e.g., Non-Travel Time to Stop).

Next, in step 1018, the data segmenting module 1000 identifies andstores Backing segments indicated by the user-selected operational dataloaded by the central server 120. According to various embodiments,Backing segments generally represent periods of time during which thevehicle 100 is moving in a reverse direction. As noted above, thetelematics device 102 may be configured to detect a vehicle event andcapture telematics data in response to the vehicle 100 beginning, orceasing, to move in a reverse direction. Accordingly, the datasegmenting module 1000 identifies Backing segments by reviewing thetelematics data in the operational data set loaded by the central server120 and identifying instances in which the vehicle 100 begins to move ina reverse direction and ceases moving in a reverse direction (e.g., byreviewing contextual data for data indicating a logged reason for datacapture was the vehicle 100 beginning or ceasing to move in a reversedirection and/or reviewing telematics data for data indicating thevehicle's direction status has changed to reverse or changed fromreverse to forward). The data segmenting module 1000 then linkschronologically adjacent Backing beginning and ending instances tocompose individual Backing segments. The data segmenting module 1000then stores the identified Backing segments in the Segmented Data Setfor use in further analyses. In one embodiment, each stored Backingsegment is defined by data indicating the segment's start time (e.g.,14:25:13), end time (e.g., 14:25:17), and segment type (e.g., Backing).

Next, in step 1020, the data segmenting module 1000 identifies andstores Seat Belt Safety Hazard segments indicated by the telematics datain the user-selected operational data set loaded by the central server120. According to various embodiments, Seat Belt Safety Hazard segmentsgenerally represent periods of time during which the a vehicle's seatbelt is disengaged while the vehicle is moving or while the vehicle'sengine is on (e.g., idling). As noted above, the telematics device 102is configured to detect a vehicle event and capture telematics data inresponse to either of these contingencies. Accordingly, the datasegmenting module 1000 identifies any Seat Belt Safety Hazard segmentsby reviewing the telematics data in the loaded operational data andidentifies data indicating instances in which the vehicle's seat belt isdisengaged while the vehicle is either (i) moving and/or (ii) the engineis on. The data segmenting module 1000 then determines individualperiods of time during which the criteria are true and composesindividual Seat Belt Safety Hazard segments. The data segmenting module1000 then stores the identified Seat Belt Safety Hazard segments in theSegmented Data Set for use in further analyses. In one embodiment, eachstored Seat Belt Safety Hazard segment is defined by data indicating thesegment's start time (e.g., 08:15:43), end time (e.g., 08:45:12), andsegment type (e.g., Seat Belt Safety Hazard—Disengaged While Traveling,Seat Belt Safety Hazard—Disengaged While Engine On).

FIG. 11 illustrates a Gantt chart 1100 populated with exemplary activitysegments identified by the data segmenting module 1000. The chart 1100illustrates vehicle and driver activity occurring between 9:30 and 10:54on a particular day, for a particular driver, and for a particularvehicle. At 9:30, an On Property segment 1101 begins, indicating that adriver is at a shipping hub and has begun preparations for the day'sdelivery. A vertical line through a medial portion of the On Propertysegment indicates that the vehicle's engine has started at 9:48, and ashort Travel segment and Backing segment 1102 are shown indicating thevehicle has been moved and then stopped. At approximately 9:53, thevehicle's engine is restarted and a Start of Trip segment 1103 isindicated. As the vehicle exits the area of the shipping hub at 9:54 tobegin deliveries, the On Property segment 1101 ends.

The vehicle continues traveling to its first stop for approximately 30minutes as indicated by the Travel segment 1104. Throughout the Travelsegment 1104, the vehicle slows to a stop and its engineidles—presumably due to intersections and traffic—as indicated byvarious Travel delay segments 1105. At approximately 10:26, the vehiclecomes to a stop and its engine is turned off, where a brief End of Tripsegment necessarily occurs, but is too brief to be visible within thescale of the chart 1100. The vehicle remains stopped from 10:16 until10:29 prior to reaching the upcoming Stop and without corresponding toany Delay or Break. As such, this period is classified as a Non-TravelTime to Stop segment 1106. The vehicle then resumes travel, stopsbriefly, and resumes travel again until arriving at the first stop at10:44. As indicated by the Stop segment 1107, the driver engages indelivery until at least 10:54 where the chart's 1100 visible time windowends. Although no Breaks, Delays, or Seat Belt Safety Hazard segmentsare detected, the chart 1100 includes linear, horizontal sectionsreserved for indicating such segments.

Employee Recap Module

As noted above in regard to FIG. 8, the start-up view of the centralserver graphical user interface 800 provides a set of evaluation optiontabs 825 associated with either the employee evaluation tab group 830 orthe location evaluation tab group 840. As each tab in the tab set 825 isassociated with a particular operational data analysis performed by oneof the modules 1000-2300, a user may request a desired analysis byselecting one the tabs in the tab set 825. As described in step 920 ofFIG. 9, in response to receiving a user-selection of one of the tabs inthe tab set 825, the central server 120 is configured to run the moduleassociated with the tab to execute the operational data analysisrequested by the user.

According to various embodiments, the employee recap module 1200 maygenerally be configured for providing a summary of performancestatistics for a particular driver on a particular day. In oneembodiment, the employee recap module 1200 is associated with anemployee recap tab 851 (shown in FIG. 13). As such, the central server120 is configured to run the employee recap module 1200 in response to auser's selection of the employee recap tab 851.

FIG. 12 illustrates steps executed by the employee recap module 1200 togenerate a performance summary for a selected driver according to oneembodiment. Beginning at step 1202, the employee recap module 1200displays an employee recap view of the central server user interface800. FIG. 13 shows an employee recap view 800A of the central serveruser interface 800 according to one embodiment. In the evaluationresults display area 820, the employee recap view 800A displays adelivery statistics table 1251, a time statistics table 1252, aperformance statistics table 1253, a miles statistics table 1254, asafety statistics table 1255, and an overall statistics table 1256.Although only tables 1251-1253 are visible in FIG. 13, a scroll barassociated with the evaluation results display area 820 allows a user tomove the display in order to view the remaining tables 1254-1256 (shownin FIG. 14). In addition, the employee recap view 800A includes a createreport button 1260 configured to generate a printable recap report(e.g., a .pdf file) showing the tables 1251-1256. FIG. 14 illustratesone embodiment of a recap report 1250 for a particular driver and dateincluding the tables 1251-1256. Furthermore, the employee recap view800A includes the various menus and options 802-809 and map display 810of the start-up view shown in FIG. 8.

Next, at step 1204, the employee recap module 1200 calculates anddisplays pickup and delivery statistics for the user-specified driverand date based on the operational data loaded by the central server 120(e.g., in step 906 of FIG. 9). In particular, the employee recap module1200 first reviews the loaded operational data and identifies dataindicating a stop was made (e.g., by searching data fields of servicedata in the loaded operational data indicating a stop has commenced orended). For each indicated stop, the employee recap module 1200determines whether the stop was a pickup or delivery, how many bills oflading were picked up or delivered, and the weight of packages orfreight picked up or delivered. In one embodiment, the employee recapmodule 1200 accomplishes this by searching data fields in the loadedoperational data associated with each identified stop and retrievingdata indicating stop type, bills of lading, and package or freightweight. The employee recap module 1200 then stores the retrieved data(e.g., in memory) and calculates the number of delivery stops, thenumber of pickup stops, the number of bills delivered, the number ofbills picked up, the combined weight of packages and/or freightdelivered, and the combined weight of packages picked up indicated bythe retrieved data. The employee recap module 1200 also calculates a sumfor the total number of stops, total number of bills, and total weightof packages and freight. The employee recap module 1200 then displaysthe results of these calculations in the delivery statistics table 1251,as shown in FIGS. 13 and 14. As such, the delivery statistics table 1251indicates the number of pickup and delivery stops made, the number ofbills of lading picked up and delivered, and the weight of freightand/or packages picked up or delivered by the user-selected driver onthe user-selected date.

Next, at step 1206, the employee recap module 1200 calculates anddisplays various time statistics for the user-specified driver and datebased on the operational data loaded by the central server 120. Theemployee recap module 1200 first reviews the loaded operational data andidentifies data indicating instances where (i) the driver has begun thework day and is on the clock, (ii) the drivers' vehicle 100 has exitedthe geo-fenced area of its respective shipping hub, (iii) the driver'svehicle 100 has entered the geo-fenced area of a designated deliveryarea, (iv) the driver's vehicle 100 has exited the geo-fenced area of adesignated delivery area, (v) the driver's vehicle 100 has entered thegeo-fenced area of its respective shipping hub, and (vi) the driver hasended the work day and is off the clock. For example, in one embodiment,the employee recap module 1200 reviews segmented data loaded by thecentral server 120 in chronological order, identifies On Property and OnArea segments presented in the loaded segmented data, and retrieves andstores the start and end time for each identified On Property and OnArea segment. The resulting stored times necessarily correspond toinstances (ii)-(v) above. Next, the employee recap module 1200 reviewsthe service data in the loaded operational data, identifies dataindicating the driver has begun or ended the work day (e.g., byreviewing logged reason for data capture fields associated with theservice data), and retrieves and stores the times associated with theseevents (e.g., by reviewing contextual data fields indicating timesassociated with the identified data). These stored times necessarilycorrespond to instances (i) and (vi) above. The various instances(i)-(vi) and their corresponding time of occurrence may be stored, forexample, in one of the central server's memory devices.

Next, the employee recap module 1200 displays identified time at whichdriver began the work day as the “Start Time” (e.g., 09:30) and theidentified time at which the driver ended the work day as the “FinishTime” (e.g., 20:56) in the appropriate row of the time statistics table1252, as shown in FIGS. 13 and 14.

Next, the employee recap module 1200 calculates and displays thedriver's “pickup and delivery hours” based on the earlier identifiedinstances. In various embodiments, pickup and delivery hours generallyrepresent the amount of time the driver was off the property of theshipping hub and engaged in pickup and delivery activity (e.g.,traveling to and from the shipping hub, time traveling between stops,and time performing pickups and deliveries at stops). Accordingly, inone embodiment, the employee recap module 1200 determines pickup anddelivery hours by calculating the total elapsed time between the endingof the first identified On Property segment (e.g., the time at which thedriver and vehicle exited the property of the shipping hub and begantraveling to the first stop) and the beginning of the last identified OnProperty segment (e.g. the time at which the driver and vehiclereentered the property of the shipping hub and after completing a numberof stops). The employee recap module 1200 then displays the result asthe “Pu+Del Hours” in the appropriate row of the time statistics table1252, as shown in FIGS. 13 and 14.

Next, the employee recap module 1200 calculates and displays thedriver's “to from hours” based on the earlier identified instances. Invarious embodiments, to from hours generally represent the amount oftime the driver and vehicle were traveling from the property of theshipping hub to a predefined delivery area (e.g., prior to completingany delivery or pickup stops) and from a predefined delivery area to theproperty of the shipping hub (e.g., after completing delivery and pickupstops). Accordingly, in one embodiment, the employee recap module 1200determines the “to from hours” for the driver by calculating the totaltime elapsed between the ending of the first identified On Propertysegment and the beginning of the first identified On Area segment, aswell as the total time elapsed between the ending of the last identifiedOn Area segment and the time beginning of the last identified OnProperty segment. The employee recap module 1200 then sums the elapsedtimes and displays the result as “To From Hours” in the appropriate rowof the time statistics table 1252, as shown in FIGS. 13 and 14.

Next, the employee recap module 1200 calculates and displays thedriver's “lag hours” based on the earlier identified instances. Invarious embodiments, the lag hours generally represent the amount oftime the driver and vehicle were preparing for deliveries on theproperty of the shipping hub before departing (pre run minutes) and theamount of time the driver and vehicle were completing a work day on theproperty of the shipping hub after returning from executing deliveries(post run minutes). Accordingly, in one embodiment, the employee recapmodule 1200 first determines and stores the total amount of pre runminutes by calculating the duration of the first identified On Propertysegment. Next, the employee recap module 1200 determines and stores thetotal amount of post run minutes by calculating the duration of the lastidentified On Property segment. The employee recap module 1200 then sumsthe values for pre run minutes and post run minutes and stores theresult as the lag hours for the driver. The employee recap module 1200then displays the “Lag Hours,” “Pre Run Minutes,” and “Post Run Minutes”in the appropriate rows of the time statistics table 1252, as shown inFIG. 14.

Next, the employee recap module 1200 calculates and displays thedriver's “on area” hours based on the earlier identified instances. Invarious embodiments, the on area hours generally represent the amount oftime the driver and vehicle are located within a predefined deliveryarea. Accordingly, in one embodiment, the employee recap module 1200determines the on area hours for the driver by calculating the durationof the identified On Area segment (or total duration of all identifiedOn Area segments if more than one is identified). The employee recapmodule 1200 then displays the result as “On Area Hours” in theappropriate row of the time statistics table 1252, as shown in FIGS. 13and 14.

Next, the employee recap module 1200 calculates and displays thedriver's “stop hours” based on the earlier identified instances. Invarious embodiments, the stop hours generally represent the total amountof time the driver has spent performing stops. Accordingly, in oneembodiment, the employee recap module 1200 reviews the loaded segmenteddata, identifies all stop segments, and sums the duration of allidentified stop segments. The employee recap module 1200 then displaysthe result as “stop hours” in the appropriate row of the time statisticstable 1252, as shown in FIG. 14.

Next, the employee recap module 1200 calculates and displays thedriver's “dispatch hours” based on the earlier identified instances. Invarious embodiments, the dispatch hours generally represent the amountof time the driver and vehicle are dispatched from the property of theshipping hub to perform deliveries and pickups. Accordingly, in oneembodiment, the employee recap module 1200 determines the dispatch hoursfor the driver by summing the previously determined values for on areahours and to from hours. The employee recap module 1200 then displaysthe result as “Dispatch Hours” in the appropriate row of the timestatistics table 1252, as shown in FIG. 14.

Next, the employee recap module 1200 retrieves and displays the “plannedon property minutes” for the driver. In one embodiment, the employeerecap module 1200 retrieves this value from the Planning Data Set storedon the central server database and displays the retrieved value in theappropriate row of the time statistics table 1252, as shown in FIG. 14.Next, the employee recap module 1200 reviews the service data in theoperational data loaded by the central server 120 and retrievesvalues—if any—for the driver's turn minutes, no run minutes,administration minutes, training minutes, and dock worker pickup anddelivery minutes; each of which may have been entered into the mobiledevice 110. The employee recap module 1200 then displays the retrievedvalues in the appropriate rows of the time statistics table 1252, asshown in FIG. 14.

Next, at step 1208, the employee recap module 1200 calculates anddisplays various performance statistics for the user-specified driverand date based on the operational data loaded by the central server 120.According to one embodiment, the employee recap module 1200 firstcalculates the driver's stops per pickup and delivery hour, stops perdispatch hour, and stop per area hour by dividing the total number ofstops (e.g., 17) by the values for pickup and delivery hours, dispatchhours, and on area hours—respectively—as determined in step 1206. Next,the employee recap module 1200 calculates the driver's bills per pickupand delivery hour, bills per dispatch hour, and bills per area hour bydividing the total number of bills (e.g., 29) by the values for pickupand delivery hours, dispatch hours, and on area hours—respectively—asdetermined in step 1206. The calculated values for stops per pickup anddeliver hour, stops per dispatch hour, stops per area hour, bills perpickup and delivery hour, bills per dispatch hour, and bills per areahour are then displayed in the performance statistics table 1253, asshown in FIG. 14.

Next, at step 1210, the employee recap module 1200 calculates anddisplays various distance statistics for the user-specified driver anddate based on the operational data loaded by the central server 120.According to one embodiment, the employee recap module 1200 firstreviews the service data in the loaded operational data and retrievesvalues for the driver's total number of trips, to from miles, on areamiles, and total miles; each of which may have been entered into themobile device 110. In another embodiment, the employee recap module 1200reviews the telematics data in the loaded operational data anddetermines values for the driver's total number of trips, to from miles,on area miles, and total miles (e.g., from odometer-derived telematicsdata) for the user-specified date. Next, the employee recap module 1200calculates the miles per stop for the driver by dividing the valuedetermined for total miles (e.g., 184) by the earlier determined valuefor total number of stops (e.g., 17). The employee recap module 1200then determines the driver's total number of GPS miles foruser-specified date based on telematics data in the loaded operationaldata (e.g., using the techniques for determining GPS miles describedherein). The employee recap module 1200 the displays the determinedvalues for total trips, to from miles, on area miles, total miles, GPSmiles, and miles per stop in the miles statistics table 1254, as shownin FIG. 14.

Next, at step 1212, the employee recap module 1200 calculates anddisplays various safety statistics for the user-specified driver anddate based on the operational data loaded by the central server 120.According to one embodiment, the employee recap module 1200 firstreviews the segmented data loaded by the central server 120 andidentifies seat belt safety hazard segments. The employee recap module1200 then sums the duration of all segments stored as Seat Belt SafetyHazard—Disengaged While Traveling and stores the result as the totalSeat Belt Off in Travel time. The employee recap module 1200 then sumsthe duration of all segments stored as Seat Belt SafetyHazard—Disengaged While Engine On and stores the result as the totalSeat Belt Off with Engine On time. The employee recap module 1200 thendisplays the determined values for “Seat Belt Off in Travel” and “SeatBelt Off with Engine On” in the appropriate rows of the of the safetystatistics table 1255, as shown in FIG. 14.

Next, the employee recap module 1200 reviews the segmented data loadedby the central server 120 and identifies vehicle backing segments. Theemployee recap module 1200 then counts the number of vehicle backingsegments and stores the result as the total number of backing events forthe driver. Next, the employee recap module 1200 determines the distancetraveled by the vehicle 100 during each identified backing segment(e.g., by reviewing corresponding telematics data indicating odometerreadings, by calculating the distance traveled based on GPS location ofthe vehicle at the beginning and end of each backing segment). Theemployee recap module 1200 then sums the distances traveled during eachbacking segment and divides this value by the total number of backingsegments. The employee recap module 1200 then stores the result as theaverage vehicle backing distance for the driver. Next, the employeerecap module 1200 determines the time elapsed during each identifiedvehicle backing segment, sums the elapsed times for the backingsegments, and stores the result as the total backing time for thedriver. The employee recap module 1200 then displays the determinedvalues for “Total Backing Events,” “Average Distance,” and “TotalBacking Time” in the appropriate rows of the safety statistics table1255.

Next, the employee recap module 1200 calculates and displays the averagevehicle speed for the user-selected driver's vehicle. In one embodiment,the employee recap module 1200 first determines the total distancetraveled by the vehicle 100 on the user-specified date (e.g., byreviewing telematics data indicating odometer or hubometer readings, byreviewing service data indicating user-entered distance data, bycalculating distance based on GPS telematics data). Next, the employeerecap module 1200 determines the total travel time for the vehicle byidentifying travel segments in the loaded segmented data and summing theduration of the identified travel segments. The employee recap module1200 then divides the total distance traveled by the vehicle by thetotal travel time and stores the result as the average speed of thevehicle. In an embodiment in which the average vehicle speed for theuser-selected driver's vehicle is calculated using the distance based onGPS telematics data, it will be recognized that GPS signal loss mayoccur during vehicle operation. This may lead to inaccurate distancedeterminations and/or the reconciling of speed data with the distancedata. To accommodate for such situations, the telematics device 102 maybe configured to continuously store temporary GPS readings and/or othertelematics data (e.g., including position, time, and speedinformation/data). In the event of a loss of GPS signal (e.g., locationinformation), the telematics device 102 may store information about thetime and location the GPS signal (e.g., location information) was lost.The telematics device 102 may also store information about the time andlocation the GPS signal (e.g., location information) wasregained/acquired. To determine the average speed for instances in whicha GPS reading are used but there was a GPS signal loss as indicated bythe telematics data, the employee recap module 1200 can exclude any timedata and distance data associated with the GPS signal loss whendetermining the average speed, for example. Thus, the employee recapmodule 1200 can divide the total distance traveled by the vehicle (whenthe GPS signal was available) by the total travel time (when the GPSsignal was available) and store the result as the average speed of thevehicle. The determination excludes the data for intermediate locationsfor which the location information was lost (e.g., based on anindication of a loss of location information associated with a firstintermediate location and an indication of an acquisition of locationinformation associated with a second intermediate location, the firstand second intermediate locations traveled en route from the originlocation to the end location). This provides a more accurate averagespeed traveled. The employee recap module 1200 then displays thedetermined value for average speed as “Average MPH” in the safetystatistics table 1255.

In another embodiment, the employee recap module 1200 may be configuredto calculate a corrected average speed. For example, the employee recapmodule 1200 first identifies travel delays in the loaded segmented data,sums the duration of the identified travel delays, and stores the resultas the total travel delay time. The employee recap module 1200 thensubtracts the total travel delay time from the vehicle's total traveltime and stores the result as the corrected travel time. Next, theemployee recap module 1200 divides the total distance traveled by thevehicle by the corrected travel time and stores and displays the resultas the corrected average speed of the

Next, at step 1214, the employee recap module 1200 calculates anddisplays overall statistics for the user-specified driver. According toone embodiment, the employee recap module 1200 first calculates thenumber of bills per stop for the driver. For example, the employee recapmodule 1200 first reviews the loaded segmented data and counts thenumber of stop segments present in the data. The employee recap module1200 then retrieves the total number of bill of lading for the driver(e.g., as determined in step 1204) and divides the total number of billsby the total number of stops. The employee recap module 1200 thendisplays the result in the overall statistics table 1256.

Next, the employee recap module 1200 reviews the service data in theloaded operational data and retrieves values for the number of freightstops, the number of driver handling units, the number of customerdeliveries the driver must bring back to the shipping hub, and thenumber of freight deliveries the driver must bring back to the shippinghub. The employee recap module 1200 then displays these values in theoverall statistics table 1256. Next, the employee recap moduledetermines the total idle time and idle percentage of engine run timefor the driver. These values may be calculated, for example, inaccordance with the methodologies described herein in relation to theemployee fuel economy module 1600. The determined the values are thendisplayed as “Total Idle Time” and “ITER %” in the overall statisticstable 1256.

Employee Timecard Module

According to various embodiments, the employee timecard module 1300 maygenerally be configured for providing stop-by-stop information for auser-selected driver and user-selected day. In one embodiment, theemployee timecard module 1300 is associated with an employee timecardtab 852 (shown in FIG. 16). As such, the central server 120 isconfigured to run the employee timecard module 1300 in response to auser's selection of the employee timecard tab 852.

FIG. 15 illustrates steps executed by the employee timecard module 1300to provide stop-by-stop information for a selected driver according toone embodiment. Beginning at step 1302, the employee timecard module1300 displays an employee timecard view of the central server userinterface 800. For example, FIG. 16 shows an employee timecard view 800Bof the central server user interface 800 according to one embodiment. Inthe illustrated embodiment, the employee timecard view 800B displays astop-by-stop information table 1351, which indicates some or all of thefollowing for each stop performed by the selected driver in uniqueinformation columns: the stop number (e.g., 1, 2, 3), the type ofstop—indicated as “Type” (e.g., delivery or “DL,” pickup or “PU,” returnto building or “RTB), the distance in miles from the previousstop—indicated as miles-to-stop or “MTS” (e.g., 18.5 miles), the timewhen the driver begins the stop—indicated as “Stop Start” (e.g.,10:44:00), the time when the driver completes the stop—indicated as“Start Finish” (e.g., 10:54:00), the total time elapsed while executingthe stop—indicated as “Stop Time” (e.g., 10.00 minutes), the timeelapsed traveling from the previous stop—indicated as time-to-stop or“TTS” (e.g., 74.00 minutes), the total time elapsed traveling from theprevious stop and executing the current stop—indicated as “Total Time”(e.g., 84.00 minutes), the amount of time the driver was on the propertyof a shipping hub during the time-to-stop period—indicated as “OnProperty” (e.g., 23.63 minutes), the amount of non-travel time to stopoccurring between the completion of the previous stop and the beginningof the current stop—indicated as “Non-Travel TTS” (e.g., 5.85 minutes),the amount of pure travel time occurring between the completion of theprevious stop and the beginning of the current stop-indicated as “PureTravel” (e.g., 45.37 minutes), the amount of lunch time occurringbetween the completion of the previous stop and beginning of the currentstop—indicated as “Lunch” (e.g., 30.00 minutes), the amount ofdriver-coded delay time occurring between the completion of the previousstop and the beginning of the current stop—indicated as “Coded Delay”(e.g., 1.50 minutes), the total number of units, such as freight orpackages, picked up or delivered at the current stop—indicated as“Handling Units” (e.g., 3 units), and the total weight of freight orpackages picked up or delivered at the current stop—indicated as“Weight” (e.g., 131 pounds). Although the Lunch, Coded Delay, HandlingUnits, and Weight columns are not visible in FIG. 16, a scroll barassociated with the evaluation results display area 820 allows a user tomove the display in order to view those columns. In addition, theemployee timecard view includes a create report button 1360 configuredto generate a printable stop-by-stop report (e.g., a .pdf file) showingthe stop-by-stop information table 1351. FIG. 17 illustrates oneembodiment of a stop-by-stop report for a particular driver and dateincluding the stop-by-stop information table 1351. Furthermore, theemployee timecard view 800B includes the various menus and options802-809 and map display 810 of the start-up view shown in FIG. 8.

Next, in step 1306, the employee timecard module 1300 reviews thesegmented data loaded by the central server 120 (e.g., in step 912 ofFIG. 9) in chronological order and identifies the first indicated stopsegment. The identified first stop segment is then defined as thecurrent stop as the employee timecard module 1300 performs steps1310-1318. Next, in step 1310, the employee timecard module 1300identifies and retrieves the stop type, stop start time, and stop finishtime for the current stop from the loaded segmented data. In addition,the employee timecard module 1300 assigns a stop number to the currentstop (e.g., by assigning “1” to the first identified stop and 2, 3, 4,etc. to successively identified stops). The employee timecard module1300 then displays the retrieved stop number, stop type, stop starttime, and stop finish time in the appropriate cells of the stop-by-stopinformation table 1351 as shown in FIGS. 16 and 17.

Next, in step 1311, the employee timecard module 1300 determines anddisplays the miles traveled to the current stop (e.g., “miles to stop”or “MTS). In one embodiment, the employee timecard module 1300determines the miles to stop by first reviewing the operational dataloaded by the central server 120 (e.g., in step 906 of FIG. 9) andretrieving telematics data that indicates the vehicle distance traveled(e.g., the vehicle's odometer reading) and that was captured at thestart of the current stop segment (e.g., when the vehicle's engine wasturned off, or when the vehicle 100 slowed to a stop immediately priorto the start of the stop segment). If the current stop segment is thefirst stop, the employee timecard module 1300 stores the retrieveddistance data as the miles to stop for the first stop segment. If thecurrent stop segment is not the first stop, the employee timecard module1300 also retrieves telematics data that indicates vehicle distancetraveled and that was captured at the end of the previous stop segment(e.g., when the vehicle's engine was started, or when the vehicle 100accelerated from standstill). The employee timecard module 1300 thensubtracts the vehicle distance traveled at the end of the previous stopfrom the vehicle distance traveled at the beginning of the current stopand stores the result as the miles to stop for the current stop. Theemployee timecard module 1300 then displays the determined miles to stopfor the current stop segment in the appropriate cell of the stop-by-stopinformation table 1351, as shown in FIGS. 16 and 17. In otherembodiments, the miles traveled to the current stop may be determinedusing telematics data (e.g., GPS vehicle position data) or service data(e.g., user entered distance data) in accordance with the varioustechniques described herein.

Next, in step 1312, the employee timecard module 1300 calculates anddisplays the stop time, time to stop, and total time for the currentstop. In one embodiment, the employee timecard module 1300 firstdetermines the stop time by calculating the difference between the stopfinish time and stop start time identified in step 1310. Next, theemployee timecard module 1300 identifies the stop finish time of thepreceding stop or, where the current stop is the first stop, the starttime of the preceding on-property segment. Next, the employee timecardmodule 1300 determines the time to stop by calculating the differencebetween the stop start time identified in step 1310 and the stop finishtime of the preceding stop (or start time of the preceding on-propertysegment). Next, the employee timecard module 1300 calculates the totaltime for the current stop by summing the calculated stop time and timeto stop. The employee timecard module 1300 then displays the calculatedstop time, time to stop, and total time in the appropriate cells of thestop-by-stop information table 1351, as shown in FIGS. 16 and 17.

Next, in step 1314, the employee timecard module 1300 calculates anddisplays the on property time, non-travel time to stop, and pure traveltime for the current stop. In one embodiment, the employee timecardmodule 1300 first reviews the loaded segmented data for any on propertysegments occurring between the stop start time of the current stop andthe stop finish time of any preceding stop (e.g., as identified in step1312). For example, where the current stop is the first stop, theemployee timecard module 1300 will recognize the On Property segmentoccurring at the beginning of the driver's day. If an On Propertysegment is identified, the employee timecard module 1300 then determinesthe start time and finish time for the identified On Property segmentand determines the On Property time—the duration of the On Propertysegment—by calculating the difference between the segment's start timeand finish time. Where multiple on property segments are identifiedbetween the stop start time of the current stop and the stop finish timeof any preceding stop, this process is repeated and the employeetimecard module 1300 sums the duration of the identified on propertysegments to determine the on property time.

The employee timecard module 1300 next reviews the loaded segmented datafor any non-travel time to stop segments occurring between the stopstart time of the current stop and the stop finish time of any precedingstop. If a non-travel time to stop segment is identified, the employeetimecard module 1300 then determines the start time and finish time forthe identified non-travel time to stop segment and determines thenon-travel time to stop—the duration of the non-travel time to stopsegment—by calculating the difference between the segment's start timeand finish time. Where multiple non-travel time to stop segments areidentified between the stop start time of the current stop and the stopfinish time of any preceding stop, this process is repeated and theemployee timecard module 1300 sums the duration of the identifiednon-travel time to stop segments to determine the non-travel time tostop.

The employee timecard module 1300 next reviews the loaded segmented datafor any travel segments occurring between the stop start time of thecurrent stop and the stop finish time of any preceding stop. If a travelsegment is identified, the employee timecard module 1300 then determinesthe start time and finish time for the identified travel segment anddetermines the pure travel time—the duration of the travel segment—bycalculating the difference between the segment's start time and finishtime. Where multiple travel segments are identified between the stopstart time of the current stop and the stop finish time of any precedingstop, this process is repeated and the employee timecard module 1300sums the duration of the identified travel segments to determine thepure travel time. The employee timecard module 1300 then displays thecalculated on property time, non-travel time to stop, and pure traveltime in the appropriate cells of the stop-by-stop information table1351, as shown in FIGS. 16 and 17.

Next, in step 1316, calculates and displays the lunch time and codeddelay time for the current stop. In one embodiment, the employeetimecard module 1300 first reviews the loaded segmented data for anylunch segments occurring between the start time of the current stop andthe finish time of a preceding stop (e.g., as identified in step 1312).If a lunch segment is identified, the employee timecard module 1300 thendetermines the start time and finish time for the identified lunchsegment and determines the lunch time—the duration of the lunchsegment—by calculating the difference between the segment's start timeand finish time.

The employee timecard module 1300 next reviews the loaded segmented datafor any coded delay segments occurring between the start time of thecurrent stop and the finish time of any preceding stop. If a coded delaysegment is identified, the employee timecard module 1300 then determinesthe start time and finish time for the identified coded delay segmentand determines the coded delay time—the duration of the coded delaysegment—by calculating the difference between the segment's start timeand finish time. Where multiple coded delay segments are identifiedbetween the start time of the current stop and the finish time of apreceding stop, this process is repeated and the employee timecardmodule 1300 sums the duration of the identified coded delay segments todetermine the coded delay time. The employee timecard module 1300 thendisplays the calculated lunch time and coded delay time in theappropriate cells of the stop-by-stop information table 1351, as shownin FIG. 17.

Next, in step 1318, the employee timecard module 1300 determines anddisplays the handling units and weight for the current stop. In oneembodiment, the employee timecard module 1300 first reviews the loadedoperational data and retrieves service data indicating the number ofunits delivered or picked at the current stop, and the weight of freightor packages delivered or picked up at the current stop. The employeetimecard module 1300 then displays the retrieved handling units andweight data in the appropriate cells of the stop-by-stop informationtable 1351, as shown in FIG. 17.

Next, in step 1320, the employee timecard module 1300 determines whetherthere are additional stops in the loaded segmented data. In oneembodiment, the employee timecard module 1300 executes step 1320 byreviewing the loaded segmented data for stop segments occurring afterthe current stop. If there is an additional stop segment, the employeetimecard module 1300 moves to step 1322 where it identifies the nextstop segment. As shown, the employee timecard module 1300 will then loopback through steps 1310-1320 and perform the aforementioned steps forthe newly identified stop segment, which would be defined as the“current stop” for executing the steps 1310-1320.

If there are no additional stop segments, the employee timecard module1300 moves to step 1324, where it determines and displays the miles tostop, total time, non-travel time to stop, pure travel time, lunch time,and coded delay time for the return to building trip. According tovarious embodiments, the return to building trip (RTB) represents thevehicle's travel from the final stop (e.g., stop no. 17 in FIG. 17) tothe vehicle's home shipping hub. In one embodiment, the employeetimecard module 1300 first reviews the loaded segmented data andidentifies the final On Property segment occurring after the finish timeof the final stop segment (e.g., an On Property segment representingtime the vehicle spends on the property of its home shipping hub at theend of a work day). The employee timecard module 1300 then retrieves thestart and finish time for the final On Property segment, as well as thetime of any engine on/off instances occurring during the final OnProperty segment.

Next, the employee timecard module 1300 determines the miles to stop forthe return to building segment by first reviewing the loaded operationaldata and retrieving telematics data that indicates the vehicle distancetraveled (e.g., the vehicle's odometer reading) and that was capturedwhen the vehicle's engine was turned off during the identified OnProperty segment. The employee timecard module 1300 then retrievestelematics data that indicates vehicle distance traveled and that wascaptured at the end of the previous stop segment (e.g., when thevehicle's engine was started, or when the vehicle 100 accelerated fromstandstill). The employee timecard module 1300 then subtracts thevehicle distance traveled at the end of the previous stop from thevehicle distance traveled at the engine-off point during the On Propertysegment and stores the result as the miles to stop for the return tobuilding segment. The employee timecard module 1300 then determines thetotal time for the return to building trip by calculating the differencebetween the final On Property segment's finish time and the finish timeof the preceding stop segment.

Next, the employee timecard module 1300 reviews the loaded segmenteddata for any non-travel time to stop segments occurring between thestart time of the final On Property segment and the finish time of thepreceding stop segment. If a non-travel time to stop segment isidentified, the employee timecard module 1300 then determines the starttime and finish time for the identified non-travel time to stop segmentand determines the non-travel time to stop—the duration of thenon-travel time to stop segment—by calculating the difference betweenthe segment's start time and finish time. Where multiple non-travel timeto stop segments are identified between the start time of the final OnProperty segment and the finish time of the preceding stop segment, thisprocess is repeated and the employee timecard module 1300 sums theduration of the identified non-travel time to stop segments to determinethe non-travel time to stop for the return to building trip.

The employee timecard module 1300 next reviews the loaded segmented datafor any travel segments occurring between the start time of the final OnProperty segment and the finish time of the preceding stop segment. If atravel segment is identified, the employee timecard module 1300 thendetermines the start time and finish time for the identified travelsegment and determines the pure travel time—the duration of the travelsegment—by calculating the difference between the segment's start timeand finish time. Where multiple travel segments are identified betweenthe start time of the final On Property segment and the finish time ofthe preceding stop segment, this process is repeated and the employeetimecard module 1300 sums the duration of the identified travel segmentsto determine the pure travel time for the return to building trip.

The employee timecard module 1300 next calculates and displays the lunchtime and coded delay time for the return to building trip. In oneembodiment, the employee timecard module 1300 first reviews the loadedsegmented data for any lunch segments occurring between the start timeof the final On Property segment and the finish time of the precedingstop segment. If a lunch segment is identified, the employee timecardmodule 1300 then determines the start time and finish time for theidentified lunch segment and determines the lunch time—the duration ofthe lunch segment—by calculating the difference between the segment'sstart time and finish time.

The employee timecard module 1300 next reviews the loaded segmented datafor any coded delay segments occurring between the start time of thefinal On Property segment and the finish time of the preceding stopsegment. If a coded delay segment is identified, the employee timecardmodule 1300 then determines the start time and finish time for theidentified coded delay segment and determines the coded delay time—theduration of the coded delay segment by calculating the differencebetween the segment's start time and finish time. Where multiple codeddelay segments are identified between the start time of the final OnProperty segment and the finish time of the preceding stop segment, thisprocess is repeated and the employee timecard module 1300 sums theduration of the identified coded delay segments to determine the codeddelay time for the return to building trip. The employee timecard module1300 then displays the determined the miles to stop, total time,non-travel time to stop, pure travel time, lunch time, and coded delaytime for the return to building trip in the appropriate cells of thestop-by-stop information table 1351, as shown in FIG. 17.

Next, at step 1326, the employee timecard module 1300 plots the each ofthe stops indicated in the stop-by-stop information table 1351 in themap display 810. In one embodiment, the employee timecard module 1300first reviews the loaded operational data and retrieves location datafor each stop in the table 1351 (e.g., by identifying location datacaptured at each respective′ stop start time or finish time). Next, theemployee timecard module 1300 plots each stop individually on the mapdisplay 810 (e.g., based on location data comprising GPS coordinatescorresponding to each stop). For example, in one embodiment, deliverystops may be represented on the map display 810 by a certain shapeand/or color (e.g., a blue square), while pickup stops are representedon the stop may display 1362 by another shape and/or color (e.g., yellowcircles). The employee timecard module 1300 then automatically zooms themap display 810 such that each of the plotted stops is visible.

Employee Gantt Module

According to various embodiments, the employee Gantt module 1400 maygenerally be configured for providing a graphical representation ofemployee and vehicle activity for a user-selected employee or vehicle onparticular day. In particular, the employee Gantt module 1400 generatesa Gantt chart of segments in the segmented data loaded by the centralserver (e.g., the segmented data loaded in step 912 of the FIG. 9). Inone embodiment, the employee Gantt module 1400 is associated with anemployee Gantt tab 853 (shown in FIG. 19). As such, the central server120 is configured to run the employee Gantt module 1400 in response to auser's selection of the employee Gantt tab 853.

FIG. 15 illustrates steps executed by the employee Gantt module 1400 togenerate a Gantt chart of employee and vehicle activity according to oneembodiment. Beginning at step 1402, the employee Gantt module 1400displays an employee Gantt view of the central server user interface800. For example, FIG. 19 shows an employee Gantt view 800C of thecentral server user interface 800 according to one embodiment. In theillustrated embodiment, the employee Gantt view 800C displays a Ganttchart 1452 and interval selector 1462. As described in greater detailbelow, the employee Gantt view 800C further includes a current timeindicator 1455, chart scroll bar 1458, current time display 1460, and avehicle position indicator 1465. Furthermore, the employee Gantt view800C includes the various menus and options 802-809 and map display 810of the start-up view shown in FIG. 8, which permit the user to navigateto select different data and different user interface views.

As shown in FIG. 19, the Gantt chart 1452 shown in the employee Ganttview 800C includes a vertical axis comprising a plurality of activitysegment rows 1453 each associated with a unique activity segment, and ahorizontal axis comprising a plurality of time markers 1454. In theillustrated embodiment, the activity segment rows 1453 are comprised ofan On Property Time row, Non-Travel Time to Stop row, Stop Time row,Travel row, Travel Delays row, Backing row, Lunch row, Delay Codes row,and Seat Belt row. According to various other embodiments, the activitysegment rows 1453 may further include unique rows for any other activitysegment identified by the data segmenting module 1000. In addition, inthe illustrated embodiment, the Gantt chart's time markers 1454 comprisea plurality of hash marks scaled to indicate one minute increments oftime. The scale of the time markers 1454—and thereby the scale of theGantt chart 1452—may be adjusted by the user via the interval selector1462 (e.g., where setting the selector to “1” sets the time markers toone minute increments, setting the selector to “5” sets the time markersto five minute increments, and so on).

Next, at step 1404, the employee Gantt module 1400 plots activitysegments in the user-selected data on the Gantt chart 1452. According toone embodiment, the employee Gantt module 1400 executes step 1404 byfirst identifying segments in the segmented data loaded by the centralserver 120 (e.g., the data loaded in step 912 of FIG. 9). The employeeGantt module 1400 then plots each identified segment in the appropriateone of the Gantt chart's activity rows 1453 based on each identifiedsegment's type (e.g., On Property, Non-Travel Time to Stop, etc.) and inthe appropriate position based on each identified segment's start andfinish time. For example, as shown in FIG. 19, the employee Gantt module1400 generates a graphical representation of each activity segmentcomprising a rectangular block having a left edge aligned with the timermarker 1454 corresponding to the activity's start time, a right edgealigned with the time marker 1454 corresponding to the activity's finishtime, and a top and bottom edges defining the segment within one of theactivity rows 1453.

In particular, at step 1404, the employee Gantt module 1400 divides OnProperty segments into block sections representing On Property timeduring which the vehicle's engine is off and On Property time duringwhich the vehicle's engine is on (e.g., by dividing the On Propertysegment block with a vertical line indicating the point at which theengine is turned on or off). In addition, in one embodiment, theemployee Gantt module 1400 presents identified Start of Trip, Travel,and End of Trip segments in the “Travel” activity row of the Gantt chart1452, the Start of Trip and End of Trip segments flanking each Travelsegment. The employee Gantt module 1400 also identifies any representedStop segments and displays the stop number (e.g., “1) and stop type(e.g., delivery or “DL) adjacent each Stop segment block. As will beappreciated from the description herein, the employee Gantt module 1400may determine the stop number and stop type using, for example, themethods described above in relation to the employee timecard module1300. Further, in one embodiment, the employee Gantt module 1400calculates the duration of each represented activity segment anddisplays the duration within the activity segment block (where the Ganttchart's resolution permits). In addition, in one embodiment, theemployee Gantt module 1400 displays the various identified activitysegments in a color-coded arrangement (e.g., all On Property segmentsare green, all Non-Travel Time to Stop segments are yellow, etc.).

According to various embodiments, the Gantt chart 1452 displays theplotted activity segments occurring during a certain time window. Forexample, in the employee Gantt view 800C shown in FIG. 19, the Ganttchart 1452 displays segments occurring between approximately 11:00 AMand 12:45 PM. As described in greater detail below, in variousembodiments, a user may adjust the time window displayed in the Ganttchart 1452 using the chart scroll bar 1458 and interval selector 1462.

Next, at step 1406, the employee Gantt module 1400 plots the path of thevehicle 100—as indicated by the user-selected data—on the map display810. According to one embodiment, the employee Gantt module 1400executes step 1406 by retrieving location data present in theoperational data loaded by the central server 120 (e.g., the data loadedin step 906), as well as corresponding data indicating the time eachindividual location data point was captured. The employee Gantt module1400 then plots each individual location data point on the map display810 and connects the plotted points in chronological order with linesrepresenting the path of the vehicle 100.

Next, at step 1408, the employee Gantt module 1400 displays and synchsthe current time indicator 1455 and the vehicle position indicator 1465.In the illustrated embodiment of FIG. 19, the current time indicator1455 comprises a vertical bar disposed on the Gantt chart 1452 at one ofthe time markers 1454. The vehicle position indicator 1465 comprises animage of a truck positioned adjacent a highlighted point along thevehicle path plotted in step 1406. According to various embodiments, thelocation of the vehicle position indicator 1465 on the map display 810corresponds to the position of the current time indicator 1455. Forexample, in FIG. 19, the current time indicator 1455 is positioned at11:44 and, thus, the vehicle position indicator 1465 is positioned atthe point along the plotted path where the vehicle 100 was located at11:44. According to one embodiment, in step 1408, the employee Ganttmodule 1400 first positions the current time indicator 1455 in a defaultposition (e.g., 10:00). Next, the employee Gantt module 1400 reviews theloaded operational data, identifies the location of the vehicle 100 atthe default time (or the location at the time nearest to the defaulttime indicated in the operational data), and places the vehicle positionindicator 1465 at the identified location on the map display 810 (e.g.,based on retrieved location data, such as GPS coordinates).

Next, at step 1410, the employee Gantt module 1400 monitors the employeeGantt view 800C of the user interface for user input requesting changesto the displayed Gantt chart 1452 and/or map display 810. For example,in the illustrated embodiment, the employee Gantt module 1400 isconfigured to monitor for user requests to change the time markintervals (e.g., via the interval selector 1462), change the time windowdisplayed by the Gantt chart 1452 (e.g., via the chart scroll bar 1458),change the current time setting (e.g., by dragging the current timeindicator 1455, dragging the vehicle position indicator 1465, orinputting a time into the current time display 1460), and change theview of the map display 810 (e.g., by zooming or panning the display).

Accordingly, at step 1412, the employee Gantt module 1400 determineswhether a user has adjusted the time window displayed by the Gantt chart1452. For example, a user may adjust the time window by moving the chartscroll bar 1458 (e.g., right to adjust the time window forward in timeand left to adjust the time window back in time). If the employee Ganttmodule 1400 has not detected an adjustment to the time window of theGantt chart 1452, it moves to step 1416. If the employee Gantt module1400 has detected a time window adjustment, it moves to step 1414. Atstep 1414, the employee Gantt module adjusts the Gantt chart 1452 todisplay activity segments within the time window corresponding to theposition of the scroll bar 1458 at any given time. For example, where auser slides the chart scroll bar 1458, the employee Gantt module 1400moves the activity segments and time intervals 1454 displayed in theGantt chart 1452 in unison with the movement of the scroll bar 1458.Likewise, where a user selects a new point along the chart scroll bar1458, the employee Gantt module 1400 automatically adjust the Ganttchart 1452 to display activity segments occurring within thecorresponding time window.

Next, at step 1416, the employee Gantt module 1400 determines whether auser has adjusted the time marker intervals. For example, a user may usethe interval selector 1462 to change the interval setting form “1”(e.g., one minute increments) to “10” (e.g., ten minute increments). Ifthe employee Gantt module 1400 has not detected an adjustment to thetime marker intervals, it moves to step 1420. If the employee Ganttmodule 1400 has detected an adjustment, it moves to step 1418. At step1418, the employee Gantt module 1400 first adjusts the scale of the timemarkers 1454 to the setting selected by the user. As adjusting the scaleof the time markers 1454 necessarily changes the time window displayedby the Gantt chart 1452, the employee Gantt module 1400 next adjusts theGantt chart 1452 to display only those segments present within the newtime window (e.g., as described above in relation to step 1414).

Next, at step 1420, the employee Gantt module 1400 determines whetherthe user has adjusted the current time setting. For example, a user mayadjust the current time setting by repositioning the current timeindicator 1455 at a particular point on the Gantt chart 1452 (e.g., byclicking on a portion of the Gantt chart 1452), dragging the currenttime indicator 1455 along the Gantt chart 1452, repositioning thevehicle position indicator 1465 at a particular point on the map display810 (e.g., by clicking on a portion of the vehicle path displayed in themap display 810, which corresponds to a particular time when the vehiclewas present at that location), dragging the vehicle position indicator1465 along the vehicle path displayed in the map display 810, orinputting a time into the current time display 1460. If the employeeGantt module 1400 has not detected an adjustment to current timesetting, it moves to step 1424. If the employee Gantt module 1400 hasdetected an adjustment, it moves to step 1422.

At step 1422, the employee Gantt module 1400 adjusts the position of thecurrent time indicator 1455 and vehicle position indicator 1465 inresponse to the user's input. For example, where the user clicks on apoint on the Gantt chart 1452 or drags the current time indicator 1455itself, the employee Gantt module 1400 first moves the current timeindicator 1455 in response to the user input and displays thecorresponding current time in the current time display 1460 (e.g., basedon the position of the current time indicator 1455 in relation to thetime markers 1454). The employee Gantt module 1400 then determines thelocation of the vehicle 100 at the new current time setting (e.g., byreviewing the loaded operational data and identifying location datacorresponding to the current time setting, or time nearest to thecurrent time setting) and repositions the vehicle position indicator1465 at the identified location on the map display 810. Likewise, wherethe user inputs a current time into the current time display 1460, theemployee Gantt module 1400 first moves the current time indicator 1455to the time marker 1454 corresponding to the input time. The employeeGantt module 1400 then determines the location of the vehicle 100 at thenew current time setting (e.g., as described above) and repositions thevehicle position indicator 1465 at the identified location on the mapdisplay 810. Similarly, where the user clicks on a point on the mapdisplay 810 or drags the vehicle position indicator 1465 itself, theemployee Gantt module 1400 first moves the vehicle position indicator1465 in response to the user input. The employee Gantt module 1400 thendetermines the location of the vehicle position indicator 1465 based onits new position on the map display 810 and determines the current timesetting corresponding to the new location (e.g., by reviewing the loadedoperational data and identifying the time data corresponding to the newlocation). The employee Gantt module 1400 then repositions the currenttime indicator 1455 in accordance with the identified current time anddisplays the new current time in the current time display 1460.

Next, at step 1424, the employee Gantt module 1400 determines whetherthe user has adjusted the view of the map display 810. For example, invarious embodiments, the map display 810 includes typical graphical mapcontrols, such as zoom-in/zoom-out buttons and a pan feature that allowsa user to click on the map display 810 itself and move the displayedgeographical area. If the employee Gantt module 1400 has not detected anadjustment to view of the map display 810, it loops back to step 1410and continues monitoring the user interface for user input requestingchanges to the current display of the employee Gantt view 800C of theuser interface. If the employee Gantt module 1400 has detected anadjustment, it moves to step 1426, where the employee Gantt module 1400adjusts the view of the map display 810 in accordance with the detecteduser input (e.g., by zooming in or out on the map or panning the view ofthe map). After completing step 1426, the employee Gantt module 1400loops back to step 1410 and continues monitoring the user interface foruser input requesting changes to the current display of the employeeGantt view 800C of the user interface.

According to various embodiments, the employee Gantt view 800C of theuser interface 800 may also include a playback button. For example, inone embodiment, the employee Gantt module 1400 is configured to animatethe vehicle position indicator 1465 in response to a user's selection ofthe playback button. In such embodiments, the employee Gantt module 1400“plays” the loaded operational and segmented data such that the currenttime indicator 1455 moves across the Gantt chart 1452 at a predefinedspeed in relation to the time markers 1454 (e.g., a real-time setting,slow motion setting, fast motion setting). As the current time indicator1455 moves across the Gantt chart 1452, the employee Gantt module 1400moves the vehicle position indicator 1465 along the vehicle path shownin the map display 810 such that the vehicle position indicator'slocation always represents the location the vehicle 100 at the timeindicated by the current time indicator 1455. As such, playback buttonallows the user to view the movement of the current time indicator 1455and vehicle position indicator 1465 simultaneously.

As noted above, the employee Gantt module 1400 displays the variousidentified activity segments in a color-coded arrangement in the Ganttchart 1464. In one embodiment, the employee Gantt module 1400 is furtherconfigured to display the vehicle position indicator 1465 at a giventime in the same color as an activity segment occurring at that time.For example, where the current time indicator 1455 is positioned over aTravel segment, the employee Gantt module 1400 will display the vehicleposition indicator 1465 in the same color as the Travel segment block inthe Gantt chart 1452. In addition, in further embodiments, the employeeGantt view 800C of the user interface 800 may also include a “print”button that allows the user to generate a report (e.g., a PDF or Excelfile) comprising one or more views of the Gantt chart 1452 and/or themap display 810.

Employee Delay Code Module

According to various embodiments, the employee delay code module 1500may generally be configured for providing delay code information for auser-selected driver and user-selected day. In one embodiment, theemployee delay code module 1500 is associated with an employee delaycode tab 854 (shown in FIG. 21). As such, the central server 120 isconfigured to run the employee delay code module 1500 in response to auser's selection of the employee delay code tab 854.

FIG. 20 illustrates steps executed by the employee delay code module1500 to provide delay code information for a selected driver accordingto one embodiment. Beginning at step 1502, the employee delay codemodule 1500 displays an employee delay code view of the central serveruser interface 800. For example, FIG. 21 shows an employee delay codeview 800D of the central server user interface 800 according to oneembodiment. In the illustrated embodiment, the employee delay code view800D displays a delay code table 1552, which indicates some or all ofthe following for each delay code entered by a driver: the delay code'stype (e.g., Exception Delay or “ED”, Bring Back or “BB), the delaycode's start time (e.g., 14:32:00), the delay code's end time (e.g.,15:02:00), the total time of the delay code (e.g., 30 minutes), a briefdescription of the delay code (e.g., Lunch, Stuck in Traffic, Waitingfor Door, Fueling Vehicle, Train Tracks, Waiting at Security, Waitingfor Freight, Waiting for Bill of Lading), and a brief description of thelocation where user was when the delay code was entered (e.g., a postaladdress, lunch, returning to yard). In addition, the employee delay codeview 800D includes the various menus and options 802-809 and map display810 of the start-up view shown in FIG. 8.

Next, at step 1504, the employee delay code module 1500 reviews thesegmented data loaded by the central server 120 (e.g., in step 912 ofFIG. 9) in chronological order and identifies the first indicated delaycode segment. The first identified delay code segment is then defined asthe current delay code as the employee delay code module 1500 performssteps 1504-1512. Next, in step 1506, the employee delay code module 1500identifies and retrieves the delay code type, start time, end time,brief description, and location for the current delay code from theloaded segmented data. The employee delay code module 1500 then displaysthe retrieved type, start time, end time, brief description, andlocation for the current delay code in the appropriate cells of thedelay code table 1552 as shown in FIG. 21.

Next, at step 1508, the employee delay code module 1500 calculates anddisplays the total time for the current delay code. For example, in oneembodiment, the employee delay code module 1500 determines the totaltime by calculating the difference between the current delay code'sstart time and finish time retrieved in step 1506. The employee delaycode module 1500 then displays the calculated total time in theappropriate cell of the delay code table 1552.

Next, at step 1510, the employee delay code module 1500 determineswhether there are additional delay codes in the loaded segmented data.In one embodiment, the employee delay code module 1500 executes step1510 by reviewing the retrieved segmented data for delay code segmentsoccurring after the current delay code. If there is an additional delaycode segment, the employee delay code module 1500 moves to step 1512where it identifies the next delay code segment and defines it as thenew current delay code. As shown in FIG. 20, the employee delay codemodule 1500 will then loop back through steps 1506-1510 and perform theaforementioned steps for the new current delay code.

If there are no additional delay code segments, the employee delay codemodule 1500 moves to step 1514, where it plots the location of eachdelay code segment identified and displayed in the delay code table1552. For example, in one embodiment, the employee delay module 1500executes step 1514 by retrieving the location data associated with eachidentified delay code segment and graphically representing each segmentby plotting an indicator (e.g., a circle or square) on the map display810. In addition, the employee delay code module 1500 may further plottravel path of the vehicle 100 on the map display 810 (e.g., using themethodologies described herein).

According to various embodiments, the employee delay code module 1500may be further configured to highlight (or otherwise identify) thelocation of a delay code segment on the map display 810 in response tothe segment being selected by a user from the delay code table 1552.Likewise, the employee delay code module 1500 may be configured tohighlight (or otherwise identify) a delay code segment on the delay codetable 1552 in response to the segment being selected by a user from themap display 810. In addition, the employee delay code module 1500 may beconfigured to sort the delay code segments shown in the delay code table1552 according to any of the attributes displayed in the table 1552. Forexample, in response to a user selecting the “total time” columnheading, the employee delay code module 1500 will group and display theidentified delay code segments according to their total time (e.g., withthe longest duration at the top of the table 1552).

In certain embodiments, the employee delay code module 1500 is furtherconfigured to identify abnormal delay code segments indicatingpotentially unauthorized vehicle operator behavior. For example, invarious embodiments, the employee delay code module 1500 may beconfigured to identify delay code segments having one or more predefineddelay code attributes that meet one or more predefined abnormalitycriteria. In one embodiment, the predefined abnormality criteria mayinclude a delay code duration that is within a certain percentage of thehighest delay code durations for operational data being assessed (e.g.,where the employee delay code module 1500 identifies the delay codeshaving the top 10% longest durations as abnormal delay codes). Inanother embodiment, the predefined abnormality criteria may include adelay code duration that exceeds a predefined duration limit associatedwith a particular delay code description (e.g., where the employee delaycode module 1500 identifies lunch delay codes exceeding 30 minutes,traffic delay codes exceeding 15 minutes, and fueling vehicle delaycodes exceeding 10 minutes). In yet another embodiment, the predefinedabnormality criteria may include a delay code segment having a starttime occurring proximate the end of a non-travel time to stop segmentand/or a delay code segment having an end time occurring proximate thebeginning of a non-travel time to stop segment (e.g., where the delaycode segments begins with one minute of the end of a non-travel time tostop segment or ends within one minute of the beginning of a non-traveltime to stop segment). In yet another embodiment, the predefinedabnormality criteria may include a delay code location (i.e., thelocation where a delay code was generated) that is more than apredefined distance from a predefined planned route associated with adriver or other vehicle operator generating the delay code (e.g., wherethe employee delay code module 1500 identifies delay codes generatedfrom the portable data acquisition 110 when the mobile device 110 islocated—based on GPS data for example—more than 100 feet from apredefined planned delivery route associated with the driver or vehicleoperator that is associated with the mobile device 110). In certainembodiments, the distance of the mobile device 110 from a predefineddelivery route may be determined using techniques analogous to thosedescribed in relation to the map update module, the off-course travelmodule, and FIGS. 45-51, which are discussed later herein.

Employee Safety Module

According to various embodiments, the central server 120 may furtherinclude an employee safety module (not shown) configured for providingvarious safety information for a user-selected driver and vehicle over adefined period of time (e.g., a user-selected day). In one embodiment,the employee safety module is associated with an employee safety tab 855(shown in FIG. 40). As such, the central server 120 is configured to runthe employee safety module in response to a user's selection of theemployee safety tab 855.

FIG. 40 shows an employee safety view 800M of the central server userinterface 800 generated by the employee safety module according to oneembodiment. As shown in FIG. 40, the employee safety module isconfigured to review operational data for a user-selected driver on auser-selected date and determine and display the start time, stopnumber, address, number of packages, stop type, duration, distance, andspeed of each of the selected driver's vehicle backing events. Accordingto various embodiments, the employee safety module may accomplish thisby reviewing the segmented data loaded by the central server 120 forbacking segments and determining the above-described information foreach individual backing segment based on the loaded operational data.

In addition, the employee safety module is configured to determine thedriver's total number of vehicle backing events, total backing distance,average backing distance, total backing time, average speed of backingevents, number of backing first exceptions, number of residentialbacking events, total distance of residential backing events, averagedistance of residential backing events, and total residential backingtime. For example, in one embodiment, the employee safety module reviewsthe segmented data loaded by the central server 120 and identifiesvehicle backing segments. The employee safety module then counts thenumber of vehicle backing segments and stores the result as the totalnumber of backing events for the driver.

Next, the employee safety module determines the distance traveled by thevehicle 100 during each identified backing segment (e.g., by reviewingcorresponding telematics data indicating odometer readings, bycalculating the distance traveled based on GPS location of the vehicleat the beginning and end of each backing segment). The employee safetymodule then sums the distances traveled during each backing segment andstores this value as the total backing distance. The employee safetymodule then divides the total backing distance value by the total numberof backing segments and stores the result as the average vehicle backingdistance for the driver. Next, the employee safety module determines thetime elapsed during each identified vehicle backing segment, sums theelapsed times for the backing segments, and stores the result as thetotal backing time for the driver. Based on the total backing time andtotal backing distance, the employee safety module then calculates theaverage backing speed for the driver and stores the result. The employeesafety module then displays these calculated statistics on the userinterface 800M.

In certain embodiments, the employee safety module is further configuredfor determining the above-described number of backing events, totalbacking distance, average distance, total backing time, and averagebacking speed statistics for specific geographical areas. For example,in the illustrated embodiment of FIG. 40, the employee safety module isconfigured for determining the number of residential backing events,total distance of residential backing events, average distance ofresidential backing events, and total residential backing time. In oneembodiment, the employee safety module determines these statistics byidentifying backing segments occurring within a residential area (e.g.,by comparing the location of the backing segments with geo-fencedresidential areas stored by the central server) and utilizing theabove-described techniques to thereafter calculate residential areaspecific statistics.

In addition, in the illustrated embodiment, the employee safety moduledetermines the number of first backing exceptions. When vehicle backingis performed prior to making a stop, the driver typically is able toview the area into which the vehicle will be backed just beforeperforming the backing. In contrast, when the backing is performed aftercompleting the stop, a safety risk may arise in the time elapsed sincethe driver last viewed the backing area (e.g., an object or individualmay move into the backing path). Accordingly, the employee safety modulemay be generally configured to identify instances in which the driverbacks a vehicle after completing a stop, as opposed to before completinga stop (herein a “backing first exception).

In various embodiments, the employee safety module may be configured toidentify backing first exceptions by comparing backing segments in theloaded segmented data to certain service data, telematics data, or both.For example, in one embodiment, the employee safety module is configuredto identify backing segments occurring shortly after a package isindicated as being delivered (e.g., identifying backing segmentsbeginning within two minutes after a package is indicated as delivered).In such embodiments, the employee safety module may identify thesebacking segments by comparing the times at which the identified backingsegments begin to package delivery times indicated by the service data.

In another embodiment, the employee safety module is configured toidentify backing segments occurring proximate to the completion of adelivery stop (e.g., identifying backing segments beginning within twominutes after a stop segment ends). In such embodiments, the employeesafety module may identify these backing segments by comparing the timesat which backing segments begin to times at which stop segments end asindicated by the service data.

In another embodiment, the employee safety module is configured toidentify backing segments occurring proximate to the ignition of thevehicle's engine (e.g., identifying backing segments beginning withintwo minutes after the vehicle's engine is started). In such embodiments,the employee safety module may identify these backing segments bycomparing the times at which backing segments begin to times at whichstart of trip segments begin as indicated by the telematics data.

Employee Fuel Economy Module

According to various embodiments, the employee fuel economy module 1600may generally be configured for providing fuel economy information basedon vehicle engine idle time for a user-selected driver or vehicle over adefined period of time (e.g., a user-selected day). In one embodiment,the employee fuel economy module 1600 is associated with an employeefuel economy tab 856 (shown in FIG. 23). As such, the central server 120is configured to run the employee fuel economy module 1600 in responseto a user's selection of the employee fuel economy tab 856.

FIG. 22 illustrates steps executed by the employee fuel economy module1600 to provide fuel economy information for a user-selected driver orvehicle according to one embodiment. Beginning at step 1602, theemployee fuel economy module 1600 displays an employee fuel economy viewof the central server user interface 800. For example, FIG. 23 shows anemployee fuel economy view 800E of the central server user interface 800according to one embodiment. In the illustrated embodiment, the employeefuel economy view 800E displays an idle segment table 1652, a fueleconomy statistics table 1654, and an idle time filter menu 1656.

As shown in FIG. 23, the idle segment table 1652 provides a list ofengine idle segments occurring during the user-defined period for theuser-selected vehicle (or vehicle associated with a user-selecteddriver). For each engine idle segment, the idle segment table 1652indicates the event number (e.g., 1, 2, 3, etc.), the start time of theidle segment (e.g., 09:48:03), the idle type indicated by the segment(e.g., Start of Trip, During Travel, End of Trip), and the duration or“idle time” of the segment (e.g., 00:08). The fuel economy statisticstable 1654 provides a plurality of Start of Trip idle segmentstatistics, During Travel idle segment statistics, End of Trip idlesegment statistics, and overall idle time statistics. For example, theStart of Trip, During Travel, and End of Trip idle segment statisticsindicate—for each idle segment type—the total number of idle segments(or “events), the total duration of idle segments, the average durationof idle segments, and the longest idle segment. In addition, the overallengine idle time statistics indicate the vehicle number of the vehiclefrom which the idle time statistics were derived, the total engine idletime, the total engine running time, the idle percentage of total engineruntime, the total number of idle time events, the amount of idle timeper GPS mile, and the maximum idle time event.

Although only a portion of the aforementioned statistics are illustratedin the fuel economy statistics table 1654 shown in FIG. 23, the employeefuel economy user interface view 800E includes a scroll bar associatedwith the table 1654 that allows a user to move the displayed table 1654in order to view the remaining statistics. Likewise, the employee fueleconomy view 800E includes a scroll bar associated with the idle segmenttable 1652 that allows a user to move the displayed table 1652 in orderto view idle segments not shown in FIG. 23. In addition, the employeefuel economy view 800E includes a create report button 1658 configuredto generate a printable fuel economy report (e.g., a .pdf or Excel®file) showing the idle segment table 1652 and fuel economy statisticstable 1654. FIG. 24 illustrates one embodiment of a printable fueleconomy report 1650 showing the fuel economy statistics table 1654 ofFIG. 23 in its entirety, and greater portion of the idle segment table1652 of FIG. 23.

Referring back to FIG. 23, the employee fuel economy view 800E furtherincludes an idle time filter menu 1656, which comprises Start of Tripsegment, During Travel segment, and End of Trip segment filter optionspresented as selectable boxes associated with idle segment type. Asnoted earlier, according to one embodiment, the data segmenting module1000 is configured to define all identified engine idle segments asStart of Trip idle segments, During Travel idle segments, or End of Tripidle segments. The idle time filter menu 1656 permits a user to definewhich of these idle segment types are analyzed and represented in theidle segment table 1652 and fuel economy statistics table 1654. Inaddition to the tables 1652, 1654 and filter menu 1656, the employeefuel economy view 800E further includes the various menus and options802-809 and map display 810 of the start-up view shown in FIG. 8.

Next, at step 1606, the employee fuel economy module 1600 reviews thesegmented data loaded by the central server 120 (e.g., in step 912 ofFIG. 9) in chronological order and identifies the first indicated engineidle segment. The identified first idle segment is then defined as thecurrent idle segment as the employee fuel economy module 1600 performssteps 1608-1612. Next, at step 1608, the employee fuel economy module1600 determines and displays the idle event number, start time, idletype, and idle time for the current idle segment. For example, in oneembodiment, the employee fuel economy module 1600 retrieves the currentidle segment's start time, end time, and idle type from the loadedsegmented data. The employee fuel economy module 1600 then determinesthe duration, or “idle time,” of the current idle segment by calculatingthe difference between the retrieved start time and stop time. Next, theemployee fuel economy module 1600 assigns an idle event number to thecurrent idle segment (e.g., by assigning “1” to the first identifiedidle segment and 2, 3, 4, etc. to successively identified idlesegments). The employee fuel economy module 1600 then displays thedetermined idle event number, start time, idle type, and idle time forthe current idle segment in the idle segment table 1652.

Next, at step 1610, the employee fuel economy module 1600 determineswhether there are additional engine idle segments in the loadedsegmented data. In one embodiment, the employee fuel economy module 1600executes step 1610 by reviewing the loaded segmented data for engineidle segments occurring after the current idle segment. If there is anadditional idle segment, the employee fuel economy module 1600 moves tostep 1612 where it identifies the next engine idle segment and definesit as the new current idle segment. As shown in FIG. 22, the employeefuel economy module 1600 will then loop back through steps 1608 and 1610and perform the aforementioned steps for the new current idle segment.

If there are no additional engine idle segments, the employee fueleconomy module 1600 moves to step 1614, where the employee fuel economymodule 1600 calculates overall idle statistics for the idle segmentsidentified and displayed in the idle segment table 1652. In oneembodiment, the employee fuel economy module 1600 executes step 1614 byfirst retrieving the user-selected vehicle number (e.g., the vehiclenumber associated with the user-selected driver as indicated in thedriver menu 806). This number is then stored as the vehicle numberassociated with the data presented in the idle segment table 1652 andfuel economy statistics table 1654. The employee fuel economy module1600 next retrieves values for the idle time of each idle segment in theidle segment table 1652 and sums the retrieved values. The employee fueleconomy module 1600 then stores this value as the total engine idletime. Next, the employee fuel economy module 1600 reviews the loadedoperational data, identifies engine-on and engine-off events indicatedby the data, and retrieves the time associated with each identifiedengine-on and engine-off event. For each identified engine-on event, theemployee fuel economy module 1600 calculates the elapsed time betweenthe engine-on event and the next corresponding engine-off event. Theemployee fuel economy module 1600 then stores each calculated elapsedtime as an engine-on segment, and sums the duration of the identifiedengine-on segments to calculate the vehicle's total engine running time.Next, the fuel economy module 1600 divides calculated total engine idletime value by the calculated total engine running time value and storesthe result as the idle percentage of total engine runtime or “ITERpercentage.” According to various embodiments, the ITER percentagerepresents the percentage of the engine's running time during which itwas idling.

Next, the employee fuel economy module 1600 counts the total number ofengine idle segments identified and displayed in the idle segment table1652. The employee fuel economy module 1600 then stores this value asthe total number of idle events. Next, the employee fuel economy module1600 reviews the loaded operational data and determines the total numberof GPS miles traveled by the vehicle 100 during the defined period(e.g., miles traveled by the vehicle on the user-selected date). Forexample, in one embodiment, the employee fuel economy module 1600reviews the loaded operational data in chronological order andidentifies the first and second data records containing location datapoints (e.g., first and second GPS coordinates). The employee fueleconomy module 1600 then calculates the linear distance between thefirst and second location points and stores the result. Next, theemployee fuel economy module 1600 identifies the next data recordcontaining a location data point (e.g., third GPS coordinates),calculates the linear distance between the second and third locationpoints, and stores the result. The employee fuel economy module 1600then repeats this process until the distance between the chronologicallyadjacent location data points in the loaded operational data has beendetermined. The employee fuel economy module 1600 then sums thedetermined distances and stores the result as the total GPS milestraveled. The employee fuel economy module 1600 then divides thecalculated total idle time value by the total GPS miles traveled valueand stores the result as the idle time per GPS mile.

In another embodiment, the employee fuel economy module 1600 may performa similar calculation based on the vehicle's odometer measurements. Forexample, the employee fuel economy module 1600 may retrieve from theloaded operational data a distance traveled value (e.g., an odometerreading) associated with the final idle segment in the idle segmenttable 1652 and stores this value as the total odometer miles traveled.The employee fuel economy module 1600 would then divide the calculatedtotal idle time value by the total odometer miles traveled value andstores the result as the idle time per odometer mile.

Next, the fuel economy module 1600 reviews the idle time values for allof the idle segments in the idle segment table 1652 and identifies thelargest single idle time value. The fuel economy module 1600 then storesthis value as the maximum idle event. Finally, as shown in FIG. 24, theemployee fuel economy module 1600 displays the determined vehiclenumber, the total engine idle time, the total engine running time, theidle percentage of total engine runtime, the total number of idle timeevents, the amount of idle time per GPS mile, and the maximum idle timeevent in the fuel economy statistics table 1654.

Next, at step 1616, the employee fuel economy module 1600 calculatesidle statistics for the Start of Trip idle segments identified anddisplayed in the idle segment table 1652. In one embodiment, theemployee fuel economy module 1600 executes step 1616 by first countingthe number of Start of Trip engine idle segments identified anddisplayed in the idle segment table 1652. The employee fuel economymodule 1600 then stores this value as the number of Start of Trip idleevents. Next, the employee fuel economy module 1600 retrieves values forthe idle time of each Start of Trip idle segment in the idle segmenttable 1652 and sums all of the retrieved values. The fuel economy module1600 then stores this value as the total idle time for Start of Tripidle events. Next, the fuel economy module 1600 divides the total idletime for Start of Trip idle events by the number of Start of Trip idleevents. The fuel economy module 1600 then stores this value as theaverage idle time for Start of Trip idle events. Next, the fuel economymodule 1600 reviews all of the values for the idle time Start of Tripidle segment and identifies the largest single idle time value. The fueleconomy module 1600 then stores this value as the maximum Start of Tripidle event. Finally, as shown in FIG. 24, the employee fuel economymodule 1600 displays the determined number of Start of Trip idlesegments, the total idle time of all Start of Trip idle segments, theaverage time of the Start of Trip idle segments, and maximum idle timefor a single Start of Trip segment.

Next, at step 1618, the employee fuel economy module 1600 calculatesidle statistics for the During Travel idle segments identified anddisplayed in the idle segment table 1652. In one embodiment, theemployee fuel economy module 1600 executes step 1618 by first countingthe number of During Travel engine idle segments identified anddisplayed in the idle segment table 1652. The employee fuel economymodule 1600 then stores this value as the number of During Travel idleevents. Next, the employee fuel economy module 1600 retrieves values forthe idle time of each During Travel idle segment in the idle segmenttable 1652 and sums all of the retrieved values. The fuel economy module1600 then stores this value as the total idle time for During Travelidle events. Next, the fuel economy module 1600 divides the total idletime for During Travel idle events by the number of During Travel idleevents. The fuel economy module 1600 then stores this value as theaverage idle time for During Travel idle events. Next, the fuel economymodule 1600 reviews all of the values for the idle time During Travelidle segment and identifies the largest single idle time value. The fueleconomy module 1600 then stores this value as the maximum During Travelidle event. Finally, as shown in FIG. 24, the employee fuel economymodule 1600 displays the determined number of During Travel idlesegments, the total idle time of all During Travel idle segments, theaverage time of the During Travel idle segments, and maximum idle timefor a single During Travel segment.

Next, at step 1620, the employee fuel economy module 1600 calculatesidle statistics for the End of Trip idle segments identified anddisplayed in the idle segment table 1652. In one embodiment, theemployee fuel economy module 1600 executes step 1620 by first countingthe number of End of Trip engine idle segments identified and displayedin the idle segment table 1652. The employee fuel economy module 1600then stores this value as the number of End of Trip idle events. Next,the employee fuel economy module 1600 retrieves values for the idle timeof each End of Trip idle segment in the idle segment table 1652 and sumsall of the retrieved values. The fuel economy module 1600 then storesthis value as the total idle time for End of Trip idle events. Next, thefuel economy module 1600 divides the total idle time for End of Tripidle events by the number of End of Trip idle events. The fuel economymodule 1600 then stores this value as the average idle time for End ofTrip idle events. Next, the fuel economy module 1600 reviews all of thevalues for the idle time End of Trip idle segment and identifies thelargest single idle time value. The fuel economy module 1600 then storesthis value as the maximum End of Trip idle event. Finally, as shown inFIG. 24, the employee fuel economy module 1600 displays the determinednumber of End of Trip idle segments, the total idle time of all End ofTrip idle segments, the average time of the End of Trip idle segments,and maximum idle time for a single End of Trip segment.

As noted earlier, the employee fuel economy view 800E further includesan idle time filter menu 1656 that permits a user to define which idlesegment types are analyzed and represented in the idle segment table1652 and fuel economy statistics table 1654. Accordingly, in variousembodiments, the employee fuel economy module 1600 is further configuredto review the settings of the idle time filter menu 1656 (e.g., byreviewing the status of each selectable box associated with idle segmentoptions) and determines the type or types of idle time segments the userhas requested to view. In accordance with the user's filter selectionsidentified, the employee fuel economy module 1600 will then take intoaccount only engine idle segments selected by the user using the idletime filter menu 1656 when generating the statistics shown in the fueleconomy statistics table 1654.

For example, the steps shown in FIG. 22 represent steps executed by theemployee fuel economy module 1600 where each of the Start of Tripsegment, During Travel segment, and End of Trip segment filter optionsof the idle time filter menu 1656 have been selected. However, as willbe appreciated from the description herein, the employee fuel economymodule 1600 may executed modified steps in accordance with differentuser filter selections. For example, in one embodiment, the employeefuel economy module 1600—in response to a user's selection of only theStart of Trip filter option and End of Trip filter option—would identifyand analyze only Start of Trip idle segments and End of Trip idlesegments in generating overall idle statistics in step 1614 and wouldskip step 1618 (as no analysis of During Travel segments would berequested). Similarly, in response to a user's selection of only theDuring Travel filter option, the employee fuel economy module 1600 wouldidentify and analyze only During Travel idle segments in generatingoverall idle statistics in step 1614 and would skip steps 1616 and 1620(as no analysis of Start of Trip or End of Trip segments would berequested).

Employee Trace Module

According to various embodiments, the employee trace module 1700 maygenerally be configured for providing time and distance information fora user-selected portion of a vehicle travel path. In particular, theemployee trace module 1700 enables a user to select a portion of avehicle travel path shown on the user interface's map display 810 (e.g.,as generated by the central server 120 in step 908 of FIG. 9) and viewinformation derived from operational data captured as the vehicletraveled along the selected portion of the travel path. In oneembodiment, the employee trace module 1700 is associated with anemployee trace tab 857 (shown in FIG. 26). As such, the central server120 is configured to run the employee trace module 1700 in response to auser's selection of the employee trace tab 857.

FIG. 25 illustrates steps executed by the employee trace module 1700 toprovide time and distance information for a user-selected portion of avehicle path according to one embodiment. Beginning at step 1702, theemployee trace module 1700 displays an employee trace view of thecentral server user interface 800. For example, FIG. 26 shows anemployee trace view 800F of the central server user interface 800according to one embodiment. In the illustrated embodiment, the employeetrace view 800F displays a path statistics table 1752, in addition tothe various menus and options 802-809 and map display 810 of thestart-up view shown in FIG. 8. As shown in FIG. 26, the path statisticstable 1752 indicates some or all of the following for the vehicle's 100movement along a user-selected portion of its travel path: a start time(e.g., the time at which the vehicle began traveling along the selectedportion of the travel path), an end time (e.g., the time at which thevehicle ceased traveling along the selected portion of the travel path),total time (e.g., the duration of the vehicle's travel along theselected portion of the travel path), and total miles (e.g., thedistance of the vehicle's travel along the selected portion of thetravel path). In addition, the employee fuel economy view 800E includesa create report button 1658 configured to generate a printable tracereport (e.g., a .pdf or Excel® file) showing, for example, the pathstatistics table 1652 and map display 810.

Next, at step 1704, the employee trace module 1700 monitors the mapdisplay 810 for user-input selecting a portion of a vehicle travel path.For example, FIG. 26 illustrates the map display 810 with a vehicletravel path 1754 corresponding to the loaded operational data displayed.In the illustrated embodiment, a user may select a portion of thevehicle travel path 1754 by providing user-input defining a geographicarea on the map display 810 and allowing the employee trace module 1700to select the portion of the vehicle travel path 1754 located within thedefined geographic area. For example, FIG. 26 shows a user-selectedgeographic area 1756, which the user may generate by clicking on aparticular point with a mouse-operated pointer and dragging the pointerto form the illustrated area 1756. In addition, the user may select aportion of the vehicle travel path 1754 by clicking on first and secondpoints along the displayed travel path 1754 in order to select theportion of the path defined between the two selected points.

Next, at step 1706, the employee trace module 1700 determines whetheruser-input selecting a portion of the vehicle travel path 1754 has beenreceived. If path selection user-input has not been detected, theemployee trace module 1700 loops back to step 1704 and continuesmonitoring for such user-input. If the path selection user-input hasbeen detected, the employee trace module 1700 moves to step 1708, whereit identifies the user-selected portion of the vehicle travel path. Forexample, where the user has provided input defining the user-selectedgeographic area 1756 of FIG. 26 (or another analogous area), theemployee trace module 1700 identifies portions of the vehicle travelpath 1754 located within the geographic area 1756 and defines thoseportions as the selected portions of the vehicle travel path 1754.Likewise, where a user directly selects portions of the vehicle travelpath 1754 (e.g., by clicking on one or more points along the path 1754),the employee trace module 1700 stores the selected portions. In anotherembodiment, the user may select a particular stop displayed on the mapand the employee trace module 1700 will automatically identify theselected portion of the vehicle path as the portion between the selectedstop and the next stop on the map. In one embodiment, after identifyingthe user-selected portion of the travel path 1754, the employee tracemodule 1700 graphically distinguishes the selected portion on the mapdisplay 810 from the remaining portions of the travel path 1754 (e.g.,by highlighting or coloring the selected portion uniquely from thetravel path 1754).

Next, at step 1710, the employee trace module 1700 determines anddisplays the start time of the vehicle's 100 movement along theuser-selected portion of the travel path 1754, the end time of thevehicle's 100 movement along the user-selected portion of the travelpath 1754, and the total elapsed time of the vehicle's 100 movementalong the user-selected portion of the travel path 1754. For example, inone embodiment, the employee trace module 1700 retrieves the loadedoperational data associated with the user-selected portion of the travelpath 1754 and identifies the earliest-occurring and latest-occurringdata points. The employee trace module 1700 then retrieves the time dataassociated with the earliest-occurring data point and stores that timeas the start time of the vehicle's 100 movement along the user-selectedportion of the travel path 1754. The employee trace module 1700 thenretrieves the time data associated with the latest-occurring data pointand stores that time as the end time of the vehicle's 100 movement alongthe user-selected portion of the travel path 1754. The employee tracemodule 1700 next calculates the difference between the determined starttime and the determined end time and stores the result as the total timeof the vehicle's 100 movement along the user-selected portion of thetravel path 1754. As shown in FIG. 26, the employee trace module 1700then displays the determined start time, end time, and total time in thepath statistics table 1752.

Next, at step 1712, the employee trace module 1700 calculates the totalmiles traveled by the vehicle 100 along the user-selected portion of thetravel path 1754. In one embodiment, the employee trace module 1700executes step 1712 by retrieving—from the loaded operational data—thevehicle distance data (e.g., a vehicle odometer measurement) associatedwith the start time and end time identified in step 1710. The employeetrace module 1700 then calculates the difference between the distancevalue associated with the end time and the distance value associatedwith the start time, and stores the result as the total miles traveledby the vehicle 100 along the user-selected portion of the travel path1754. As shown in FIG. 26, the employee trace module 1700 next displaysthe determined miles traveled in the path statistics table 1752.

Employee Work Area Module

According to various embodiments, the central server 120 may furtherinclude an employee work area module (not shown) configured forproviding various delivery information associated with a defined workarea for a user-selected driver and vehicle over a defined period oftime (e.g., a user-selected day). In one embodiment, the employee workarea module is associated with an employee work area tab 858 (shown inFIG. 41). As such, the central server 120 is configured to run theemployee work area module in response to a user's selection of theemployee work area tab 858.

FIG. 41 shows an employee work area view 800N of the central server userinterface 800 generated by the employee work area module according toone embodiment. As shown in FIG. 41, the employee work area module isconfigured to permit a user to define a particular geographic work areaand view delivery information associated with the selected driver anddate for that work area. For example, in one embodiment, the user maydraw one or more work areas on the map portion of the central serveruser interface (e.g., as shown in FIG. 41). In further embodiments, theuser may predefine work areas, such as a particular neighborhood orshopping district. The user may then select one or more work areas toview delivery information for.

Accordingly, in various embodiments, the employee work area module isconfigured to determine various delivery statistics associated withdefined work areas for the selected driver. As shown in FIG. 41, theemployee work area module defines a “trip” for each work area, the tripbeginning with an entry time when the driver enters the work area andending with an exit time when the driver exits the work area. For eachtrip, the employee work area module determines the trip number, drivername, route number, miles traveled, total number of stops made, numberof delivery stops made, number of driver release stops, number ofpackages delivered, number of pickup stops made, number of packagespicked up, planned delivery hours, planned pickup hours, planned travelhours, total planned time, actual trip time, over under actual vs.planned trip time, and break time. In addition, for each stop made bythe driver on the selected date, the employee work area moduledetermines and displays the trip number the stop was made in, the drivername, the stop number, the stop type, the time of the stop, the time tothe stop, the miles to the stop, the over under actual stop time toplanned stop time, the number of packages picked up or delivered, theaddress of the stop, the loop or route number, the unit number, sequencenumber, and stop class (e.g., ground, next day air, etc.).

In addition, as shown in FIG. 41, the information displayed in theemployee work area view 800N may be filtered. For example, a user mayselect to show work area labels for one or more of the work area name,over-under, distance (e.g., miles, KM), plan hours total, total stops,delivery stops, driver release stops, pickup stops, next day air stops,number of delivery packages, number of pickup packages, planned deliveryhours, planned pickup hours, planned travel hours, and break hours. Inaddition, a user may select to show work area data for any combinationof drivers, trips, over-under threshold, distance threshold, plan hourstotal threshold, total stop threshold, delivery stops, driver releasestops, pickup stops, next day air stops, delivery package threshold,pickup package threshold, plan delivery hours threshold, planned pickuphours threshold, planned travel hours threshold, and break hoursthreshold.

Location Performance Module

According to various embodiments, the location performance module 1800may generally be configured for providing delivery performancestatistics for a user-selected group of drivers (e.g., driversassociated with a user-selected hub location) during a user-selectedperiod (e.g., a particular day). In one embodiment, the locationperformance module 1800 is associated with a location performance tab861 (shown in FIG. 28). As such, the central server 120 is configured torun the location performance module 1800 in response to a user'sselection of the location performance tab 861.

FIG. 27 illustrates steps executed by the location performance module1800 to generate delivery performance statistics for a group of driversaccording to one embodiment. Beginning at step 1801, the locationperformance module 1800 displays a location performance view of thecentral server user interface 800. For example, FIG. 28 shows a locationperformance view 800G of the central server user interface 800 accordingto one embodiment. In the illustrated embodiment, the locationperformance view 800G displays a delivery performance statistics table1852, which indicates some or all of the following performancestatistics for each driver in the user-selected driver group on theuser-selected date: the number of delivery stops performed, the numberof pickup stops performed, the total number of stops performed, thetotal number of bills of lading (herein “bills) associated with items(e.g., packages or freight) picked up or delivered, the total weight ofitems picked up or delivered, the number of stops performed per hour,the average time of performed stops, the number of bills per hour, thetotal number of miles traveled, and the number of miles traveled perstop. In addition, the location performance view 800G includes thevarious menus and options 802-809 and map display 810 of the start-upview shown in FIG. 8. Furthermore, the location performance view 800Gincludes a create report button 1854 configured to generate—in responseto a user's selection—a printable location performance report (e.g., a.pdf or .xls file) showing the delivery performance statistics table1852.

Next, at step 1802, the location performance module 1800 identifies anddisplays the first driver associated with the user-selected location.For example, in one embodiment, the location performance module 1800reviews the list of drivers in the driver menu 806, identifies the firstlisted driver, and displays the driver and associated vehicle number inthe delivery performance statistics table 1852. The location performancemodule 1800 then defines the identified driver as the “current” driverfor performing steps 1804-1812. Next, at step 1803, the locationperformance module 1800 retrieves data associated with the currentdriver from the loaded operational data (e.g., the operational dataloaded by central server 120 in step 906 of FIG. 9) and loaded segmenteddata (e.g., the segmented data loaded by the central server 120 in step912 of FIG. 9), and stores the retrieved data (e.g., in the centralserver's memory) for use in performing steps 1804-1810. As theoperational data and segmented data loaded by the central server 120correspond to the user-selected date, the data retrieved in step 1803 isrepresentative of the identified driver's performance on theuser-selected date.

Next, at step 1804, the location performance module 1800 determines anddisplays the number of delivery stops, pickup stops, and total stopsperformed by the current driver on the user-selected date. In oneembodiment, the location performance module 1800 executes step 1804 byreviewing the segmented data retrieved in step 1803, counting the numberof delivery stops and the number of pickup stops, and storing thosevalues as the number of preformed delivery stops and pickup stops forthe current driver. The location performance module 1800 next sums thedetermined number of delivery stops and the determined number of pickupstops, and stores the result as the number of total stops for thecurrent driver. As shown in FIG. 28, the location performance module1800 then displays the determined number of delivery stops, number ofpickup stops, and total number of stops for the current driver in thedelivery performance statistics table 1852.

Next, at step 1806, the location performance module 1800 determines anddisplays the total number of bills associated with items (e.g., freightor packages) delivered or picked up by the current driver, the totalnumber of handling units (e.g., an individual parcel or portion offreight) delivered or picked up by the current driver, and the totalweight of the items picked up or delivered by the current driver. In oneembodiment, the location performance module 1800 executes step 1806 byfirst reviewing the operational data retrieved in step 1803, identifyingall data indicating a number of bills associated with a stop, summingthe identified bills values, and storing the result as the number ofbills delivered and picked up by the current driver. Next, the locationperformance module 1800 reviews the operational data retrieved in step1803, identifies all data indicating a number of handling unitsassociated with a stop, sums the identified handling unit values, andstores the result as the total number of handling units delivered andpicked up by the current driver. Next, the location performance module1800 reviews the operational data retrieved in step 1803, identifiesdata indicating the weight of items associated with a stop, sums theidentified weight values, and stores the result as the total weight ofitems delivered and picked up by the current driver. As shown in FIG.28, the location performance module 1800 then displays the determinednumber of bills, number of handling units, and weight for the currentdriver in the delivery performance statistics table 1852.

Next, at step 1808, the location performance module 1800 determines anddisplays the number of stops performed by the current driver per hour,the average time of stops performed by the current driver, and number ofbills delivered or picked up per hour by the current driver. In oneembodiment, the location performance module 1800 executes step 1808 byfirst reviewing the segmented data retrieved in step 1803 andidentifying the start time of the first indicated activity segment andthe stop time of the last indicated activity segment. The locationperformance module 1803 then calculates the difference between theidentified start time and stop time and stores the result as the totalworked time for the current driver. In certain embodiments, the locationperformance module 1800 may be further configured to identify any lunchand break segments in the retrieved segmented data, determine theduration of those segments, and modify the total worked time bysubtracting the identified lunch/break time.

Next, the location performance module 1800 reviews the segmented dataretrieved in step 1803 and identifies every stop segment indicated inthe retrieved segmented data. The location performance module 1800 thencounts the identified stop segments and stores the result as the totalnumber of stop segments for the current driver. In addition, thelocation performance module 1800 determines the stop time for eachidentified stop segments (e.g., using the methods described earlier inrelation to the employee timecard module 1300), sums the identified stoptimes, and stores the result as the total stop time for the currentdriver.

Next, the location performance module 1800 divides the total number ofstop segments by the total worked time, and stores the result as thestops per hour for the current driver. Further, the location performancemodule 1800 divides the total stop time by the total number of stopsegments, and stores the result as the average stop time for the currentdriver. In addition, the location performance module 1800 divides thetotal number of bills delivered or picked up (as identified in step1806) by the total worked time, and stores the result as the bills perhour for the current driver. As shown in FIG. 28, the locationperformance module 1800 then displays the determined stops per hour,average stop time, and bills per hour for the current driver in thedelivery performance statistics table 1852.

Next, at step 1810, the location performance module 1800 determines anddisplays the miles traveled by the current driver and miles traveled perstop for the current driver. In one embodiment, the location performancemodule 1800 executes step 1810 by first identifying in the operationaldata retrieved in step 1803 the last recorded value for distancetraveled (e.g., an odometer reading) storing this value as the totalmiles traveled for the current driver. The location performance module1800 then divides the total miles traveled by the total number of stops,and stores the result as the miles per stop for the current driver. Asshown in FIG. 28, the location performance module 1800 then displays thedetermined miles and miles to stop values in the delivery performancestatistics table 1852.

Next, at step 1812, the location performance module 1800 determineswhether there are additional drivers associated with the user-selectedlocation. For example, in one embodiment, the location performancemodule 1800 is configured to initially generate delivery performancestatistics for various drivers in the order that they appear in thedriver menu 806. Accordingly, in step 1812, the location performancemodule 1800 reviews the list of drivers in the driver menu 806 anddetermines whether there is at least one additional driver listed afterthe current driver. If the location performance module 1800 determinesthere are no additional drivers, the location performance module 1800moves to step 1816, which his described in greater detail below. If thelocation performance module 1800 determines there are additional driversassociated with the user-selected location, the location performancemodule 1800 moves to step 1814. In step 1814, the location performancemodule 1800 identifies and displays the next driver listed in the drivermenu 806. As in step 1802, the location performance module 1800 reviewsthe list of drivers in the driver menu 806, identifies the next listeddriver, and displays the driver and associated vehicle number in thedelivery performance statistics table 1852. The location performancemodule 1800 then defines the newly identified driver as the “current”driver. As shown in FIG. 27, the location performance module 1800 thenloops back and performs steps 1803-1812 for the newly identified currentdriver.

Next, at step 1816, the location performance module 1800 monitors thecentral server user interface 800 for a user's selection of one of thestatistical categories displayed in the delivery performance statisticstable 1852 (e.g., delivery stops, pickup stops, total stops, etc.). Forexample, in one embodiment, the location performance view 800G of thecentral server user interface 800 is configured such that eachstatistics category heading in the delivery performance statistics table1852 is a button selectable by a user (e.g., by clicking using amouse-controlled pointer). As such, the location performance module 1800is configured to recognize a user's selection of any one of the table'sheadings.

Accordingly, at step 1818, the location performance module 1800determines whether the user has selected one of the statisticalheadings. If the location performance module 1800 has not detected auser selection, it continues monitoring for user selections in step1816. If the location performance module 1800 has detected a userselection, it moves to step 1820 where it arranges the list of driversand their associated statistical data according to the selectedstatistical category. In one embodiment, in response to a user'sselection of a statistical category, the location performance module1800 reviews the values displayed in the column associated with theselected category, arranges the values numerically in order from leastto greatest (or greatest to least), and displays the each row of driverstatistics in order according to the values in the selected category.For example, in the location performance view 800G shown in FIG. 28, auser has selected the “stops per hour” statistical category.Accordingly, the location performance module 1800 has arranged thestatistics shown in the delivery performance statistics table 1852according to that category, where the driver the lowest number of stopsper hour is displayed first and the driver with the highest number ofstops per hour is shown last.

As noted earlier, the drivers listed in the driver menu 806 are eachassociated with the user-selected location (e.g., the location specifiedin the location pull-down menu 802). Accordingly, the locationperformance module 1800 permits a user-via the location performance view800G of the central server user interface 800—to compare drivers from acommon location based on the various aforementioned delivery performancestatistics.

Location Hours Module

According to various embodiments, the location hours module 1900 maygenerally be configured for providing various time statistics for auser-selected group of drivers (e.g., drivers associated with auser-selected hub location) during a user-selected period (e.g., aparticular day). In one embodiment, the location hours module 1900 isassociated with a location hours tab 862 (shown in FIG. 30). As such,the central server 120 is configured to run the location hours module1900 in response to a user's selection of the location hours tab 862.

FIG. 29 illustrates steps executed by the location hours module 1900 togenerate time statistics for a group of drivers according to oneembodiment. Beginning at step 1902, the location hours module 1900displays a location hours view of the central server user interface 800.For example, FIG. 30 shows a location hours view 800H of the centralserver user interface 800 according to one embodiment. In theillustrated embodiment, the location hours view 800H displays a timestatistics table 1952, which indicates some or all of the following timestatistics for each driver in the user-selected driver group on theuser-selected date: the driver's geofence on property time, the driver'sactual on property time, the difference between the geofence and actualon property time, the planned on property time, the excess on propertytime, the difference between the geofence on property time and plannedon property time, the driver's total non-travel time to stop time, thedriver's total delay code time, and the driver's total lunch time. Inaddition, the location hours view 800H includes the various menus andoptions 802-809 and map display 810 of the start-up view shown in FIG.8. Furthermore, the location hours view 800H includes a create reportbutton 1954 configured to generate—in response to a user's selection—aprintable location hours report (e.g., a .pdf or .xls file) showing thetime statistics table 1952.

Next, at step 1904, the location hours module 1900 identifies anddisplays the first driver associated with the user-selected location.For example, in one embodiment, the location hours module 1900 reviewsthe list of drivers in the driver menu 806, identifies the first listeddriver, and displays the driver in the time statistics table 1952. Thelocation hours module 1900 then defines the identified driver as the“current” driver for performing steps 1906-1922. Next, at step 1906, thelocation hours module 1900 retrieves the data associated with thecurrent driver from the loaded operational data (e.g., the operationaldata loaded by central server 120 in step 906 of FIG. 9) and loadedsegmented data (e.g., the segmented data loaded by the central server120 in step 912 of FIG. 9), and stores the retrieved data (e.g., in thecentral server's memory) for use in performing steps 1906-1922. As theoperational data and segmented data loaded by the central server 120correspond to the user-selected date, the data retrieved in step 1906 isrepresentative of the identified driver's performance on theuser-selected date.

Next, at step 1908, the location hours module 1900 determines anddisplays the geofence on property time and actual on property time forthe current driver on the user-selected date. In certain embodiments,the location hours module 1900 may determine both geofence on propertytime and/or actual on property time based on the segmented dataretrieved in step 1906 (depending on the configuration of the datasegmenting module 1000 and whether it has been configured to identify onproperty segments based on geofenced telematics data, service data, orboth). In various other embodiments, the location hours module 1900determines the geofenced on property time for the driver using thegeofenced, telematics-data-based on property time determining techniquesdescribed herein, such as those noted in relation to the data segmentingmodule 1000. Likewise, in such embodiments, the location hours module1900 determines the actual on property time for the driver using thedelivery-data-based on property time determining techniques describedherein, such as those noted in relation to the data segmenting module1000. The location hours module 1900 then displays the determinedgeofenced on property time and actual on property time in the timestatistics table 1952, as shown in FIG. 30.

Next, at step 1912, the location hours module 1900 determines anddisplays the difference between the geofence on property time and actualon property time determined in step 1908 for the current driver. In oneembodiment, the location hours module 1900 subtracts the determinedactual on property time from the determined geofence on property timeand displays the result in the time statistics table 1952. Next, at step1914, the location hours module 1900 retrieves the planned on propertytime for the current driver (e.g., from the Planning Data Set stored onthe central server database) and displays the planned on property timein the time statistics table 1952.

Next, at step 1916, the location hours module 1900 determines the excesson property time for the current driver by subtracting the planned onproperty time retrieved in step 1914 from the actual on property timedetermined in step 1908. The location hours module 1900 then displaysthe result in the time statistics table 1952. Next, at step 1918, thelocation hours module 1900 determines the difference between thegeofence on property time and planned on property time for the currentdriver by subtracting the planned on property time retrieved in step1914 from the geofence on property time determined in step 1908. Thelocation hours module 1900 then displays the result in the timestatistics table 1952.

Next, at step 1920, the location hours module 1900 determines the totalnon-travel time to stop time, delay code time, and lunch time for thecurrent driver on the user-selected date. In one embodiment, thelocation hours module 1900 determines each of these values by reviewingthe segmented data retrieved in step 1906, summing the duration of theidentified non-travel time to stop segment, summing the duration of theidentified delay code segments, and summing the duration of theidentified lunch segments. The location hours module 1900 then displaysthe results in the time statistics table 1952.

Next, at step 1922, the location hours module 1900 determines whetherthere are additional drivers associated with the user-selected location.For example, in one embodiment, the location hours module 1900 isconfigured to initially generate time statistics for various drivers inthe order that they appear in the driver menu 806. Accordingly, in step1922, the location hours module 1900 reviews the list of drivers in thedriver menu 806 and determines whether there is at least one additionaldriver listed after the current driver. If the location hours module1900 determines there are additional drivers associated with theuser-selected location, the location hours module 1900 moves to step1924. In step 1924, the location hours module 1900 identifies anddisplays the next driver listed in the driver menu 806. As in step 1904,the location hours module 1900 reviews the list of drivers in the drivermenu 806, identifies the next listed driver, and displays the driver inthe time statistics table 1952. The location hours module 1900 thendefines the newly identified driver as the “current” driver. As shown inFIG. 29, the location hours module 1900 then loops back and performssteps 1906-1922 for the newly identified current driver.

Location Idle Time Module

According to various embodiments, the location idle time module 2000 maygenerally be configured for providing efficiency statistics based onengine idle time for a user-selected group of drivers. In oneembodiment, the location idle time module 2000 is associated with alocation idle time tab 863 (shown in FIG. 32). As such, the centralserver 120 is configured to run the location idle time module 2000 inresponse to a user's selection of the location idle time tab 863.

FIG. 31 illustrates steps executed by the location idle time module 2000to generate idle time efficiency statistics for a group of driversaccording to one embodiment. Beginning at step 2002, the location idletime module 2000 displays a location idle time view of the centralserver user interface 800. For example, FIG. 32 shows a location idletime view 800I of the central server user interface 800 according to oneembodiment. In the illustrated embodiment, the location idle time view800I displays an idle time efficiency table 2052, in addition to thevarious menus and options 802-809 and map display 810 of the start-upview shown in FIG. 8.

In various embodiments, the idle time efficiency table 2052 indicatessome or all of the following efficiency statistics for each respectivevehicle associated with each driver in the user-selected driver group onthe user-selected date: an id number indicating the vehicle associatedwith the driver on the user-selected date, the vehicle's total idletime, the vehicle's idle percentage of engine runtime, the vehicle'smaximum engine idle event, the vehicle's total Start of Trip idle time,the vehicle's total During Travel idle time, the vehicle's End of Tripidle time, the vehicle's total combined Start of Trip and End of Tripidle time, the vehicle's Start of Trip and End of Trip over/under time,the vehicle's Start of Trip idle time per idle event, the vehicle's Endof Trip idle time per idle event, the vehicle's total idle time per GPSmile, the vehicle's Travel Delay idle time per GPS mile, and the totaltime in which the driver's seat belt was disengaged while the vehiclewas idling.

Although only a portion of the aforementioned statistics are illustratedin the idle time efficiency table 2052 shown in FIG. 32, the locationidle time user interface view 800I includes a scroll bar associated withthe table 2052 that allows a user to move the displayed table 2052 inorder to view the remaining statistics. In addition, the location idletime view 800I includes a create report button 2054 configured togenerate—in response to a user's selection—a printable location idletime report (e.g., a .pdf or .xls file) showing the idle time efficiencytable 2052. FIG. 33 illustrates one embodiment of a printable locationidle time report 2050 showing the idle time efficiency table's 2052statistical categories.

Next, at step 2004, the location idle time module 2000 identifies anddisplays the first driver and vehicle associated with the user-selectedlocation. For example, in one embodiment, the location idle time module2000 reviews the list of drivers in the driver menu 806, identifies thefirst driver and the vehicle associated with the first driver, anddisplays the driver and id number of the associated vehicle in the idletime efficiency table 2052. The location idle time module 2000 thendefines the identified driver and vehicle as the “current” driver andvehicle for performing steps 2006-2024.

Next, at step 2006, the location idle time module 2000 retrieves dataassociated with the current driver and vehicle from the loadedoperational data (e.g., the operational data loaded by the centralserver 120 in step 906 of FIG. 9) and loaded segmented data (e.g., thesegmented data loaded by the central server 120 in step 912 of FIG. 9),and stores the retrieved data (e.g., in the central server's memory) foruse in performing steps 2008-2024. As the operational data and segmenteddata loaded by the central server 120 correspond to the user-selecteddate, the data retrieved in step 2006 is representative of theidentified driver's performance on the user-selected date.

Next, at step 2008, the location idle time module 2000 determines anddisplays the total engine idle time for the current vehicle on theuser-selected date. In one embodiment, the location idle time module2000 executes step 2008 by reviewing the segmented data retrieved instep 2006, identifying every idle segment present in the segmented data,and determines the duration of each identified idle segment (e.g., usingthe methods described earlier in relation to the employee fuel economymodule 1600). The location idle time module 2000 then sums the durationsof the identified idle segments and stores the result as the total idletime for the current vehicle and driver. As shown in FIGS. 32 and 33,the location idle time module 2000 then displays the determined totalidle time value in the idle time efficiency table 2052.

Next, at step 2010, the location idle time module 2000 determines anddisplays the idle percentage of engine runtime for the current vehicleon the user-selected date. In one embodiment, the location idle timemodule 2000 executes step 2010 by first reviewing the operational dataretrieved in step 2006, identifying the engine-on and engine-off eventsindicated by the data, and retrieving the time associated with eachidentified engine-on and engine-off event. For each identified engine-onevent, the location idle time module 2000 then calculates the elapsedtime between the engine-on event and the next corresponding engine-offevent. The location idle time module 2000 then stores each calculatedelapsed time as an engine-on segment, and sums the duration ofidentified engine-on segments to calculate the vehicle's total enginerunning time. Next, the location idle time module 2000 divides the totalidle time value determined in step 2008 by the calculated total enginerunning time value and stores the result as the idle percentage of totalengine runtime or “ITER percentage.” As shown in FIGS. 32 and 33, thelocation idle time module 2000 then displays the determined ITERpercentage in the idle time efficiency table 2052.

Next, at step 2012, the location idle time module 2000 determines anddisplays the maximum idle event for the current vehicle on theuser-selected date. In one embodiment, the location idle time module2000 executes step 2012 by reviewing the duration values-determined instep 2008—for every idle segment present in the segmented data retrievedin step 2006. The location idle time module 2000 then identifies thelongest duration value associated with an idle segment in the retrievedsegmented data and stores the result as the maximum idle event for thecurrent driver and vehicle. As shown in FIGS. 32 and 33, the locationidle time module 2000 then displays the determined maximum idle event inthe idle time efficiency table 2052.

Next, at step 2014, the location idle time module 2000 determines anddisplays the Start of Trip idle time, During Travel idle time, and Endof Trip idle time for the current driver and vehicle. In one embodiment,the location idle time module 2000 executes step 2014 by firstretrieving values for the idle time of each Start of Trip idle segmentpresent in the segmented data retrieved in step 2006. The location idletime module 2000 then sums the retrieved values and stores the result asthe total Start of Trip idle time for the current driver and currentvehicle. This procedure is then repeated for the During Travel and Endof Trip idle segments in the retrieved segmented data to determine thetotal During Travel idle time and total End of Trip idle time,respectively. As shown in FIGS. 32 and 33, the location idle time module2000 next displays the determined Start of Trip idle time, During Travelidle time, and End of Trip idle time in the idle time efficiency table2052.

Next, at step 2016, the location idle time module 2000 determines anddisplays the combined Start of Trip and End of Trip idle time, andover/under for the Start of Trip and End of Trip idle time for thecurrent driver and vehicle. In one embodiment, the location idle timemodule 2000 executes step 2016 by summing the Start of Trip idle timeand End of Trip idle time values determined in step 2014, and storingthe result as the Start of Trip and End of Trip total idle time. Thelocation idle time module 2000 then determines an over/under value forthe Start of Trip and End of Trip idle time by counting the total numberof start of trip and end of trip segments, multiplying this number by apredefined, planned allocated time for each segment (e.g., 10 seconds),and subtracting this number form the combined Start of Trip and End ofTrip total idle time. As shown in FIGS. 32 and 33, the location idletime module 2000 next displays the determined Start of Trip and End ofTrip combined idle time and the Start of Trip and End of Trip over/undervalue in the idle time efficiency table 2052.

Next, at step 2018, the location idle time module 2000 determines anddisplays the Start of Trip time per idle event and the End of Trip timeper idle event for the current driver and vehicle. In one embodiment,the location idle time module 2000 executes step 2018 by first countingthe number of Start of Trip engine idle segments identified in theretrieved segmented data and storing this value as the number of Startof Trip idle events. Next, the location idle time module 2000 dividesthe total Start of Trip idle time (calculated in step 2014) by thenumber of Start of Trip idle events. The location idle time module 2000then stores this value as the Start of Trip time (e.g., seconds) perStart of Trip idle event. The location idle time module 2000 thenrepeats this procedure for End of Trip idle time segments in theretrieved segmented data and stores the result as the End of Trip timeper End of Trip idle event. As shown in FIG. 33, the location idle timemodule 2000 next displays the determined Start of Trip time per eventand End of Trip time per event values in the idle time efficiency table2052.

Next, at step 2020, the location idle time module 2000 determines anddisplays the total idle time per GPS mile for the current driver andvehicle. In one embodiment, the location idle time module 2000 executesstep 2020 by first reviewing the operational data retrieved in step 2006and determining the total number of GPS miles traveled by the vehicle100 on the user-selected date. For example, the location idle timemodule 2000 reviews the retrieved operational data in chronologicalorder and identifies the first and second data records containinglocation data points (e.g., first and second GPS coordinates). Thelocation idle time module 2000 then calculates the linear distancebetween the first and second location points and stores the result.Next, the location idle time module 2000 identifies the next data recordcontaining a location data point (e.g., third GPS coordinates),calculates the linear distance between the second and third locationpoints, and stores the result. The location idle time module 2000 thenrepeats this process until the distance between chronologically adjacentlocation data points in the retrieved operational data has beendetermined. The location idle time module 2000 then sums the determineddistances and stores the result as the total GPS miles traveled for thecurrent driver and vehicle. Next, the location idle time module 2000divides the total idle time value calculated in step 2008 by the totalGPS miles traveled value and stores the result as the total idle timeper GPS mile for the current driver and vehicle. The location idle timemodule 2000 then divides the total During Travel idle time valuecalculated in step 2014 by the total GPS miles traveled value and storesthe result as the travel delays per GPS mile for the current driver andvehicle. As shown in FIG. 33, the location idle time module 2000 nextdisplays the determined total idle time per GPS mile and travel delaysper GPS mile for the current driver and vehicle in the idle timeefficiency table 2052.

Next, at step 2022, the location idle time module 2000 determines anddisplays the total time in which the driver's seat belt was disengagedwhile the vehicle was idling. In one embodiment, the location idle timemodule 2000 executes step 2022 reviewing the segmented data retrieved instep 2006 and identifying every Seat Belt Safety Hazard segment in thesegmented data. The location idle time module 2000 then determines theduration of each identified Seat Belt Safety Hazard segments (e.g.,using the methods for determining segment duration described herein).Next, the location idle time module 2000 sums the durations of theidentified Seat Belt Safety Hazard segments and stores the result as thetotal seat belt off while idling time for the current driver andvehicle. As shown in FIG. 33, the location idle time module 2000 thendisplays the determined total seat belt off while idling time for thecurrent driver and vehicle in the idle time efficiency table 2052.

Next, at step 2024, the location idle time module 2000 determineswhether there are additional drivers associated with the user-selectedlocation. For example, in one embodiment, the location idle time module2000 is configured to initially generate idle time efficiency statisticsfor various drivers in the order that they appear in the driver menu806. Accordingly, in step 2024, the location idle time module 2000reviews the list of drivers in the driver menu 806 and determineswhether there is at least one additional driver listed after the currentdriver. If the location idle time module 2000 determines there areadditional drivers associated with the user-selected location, thelocation idle time module 2000 moves to step 2026. In step 2026, thelocation idle time module 2000 identifies and displays the next driverlisted in the driver menu 806. As in step 2004, the location idle timemodule 2000 reviews the list of drivers in the driver menu 806,identifies the next listed driver, and displays the driver andassociated vehicle number in the idle time efficiency table 2052. Thelocation idle time module 2000 then defines the newly identified driveras the “current” driver. As shown in FIG. 31, the location idle timemodule 2000 then loops back and performs steps 2006-2024 for the newlyidentified current driver.

Although not shown in the steps of FIG. 31, in certain embodiments thelocation idle time module 2000 may be configured to monitor the centralserver user interface 800 for a user's selection of one of thestatistical categories displayed in the idle time efficiency table 2052(e.g., total idle time, max idle event, etc.). For example, in oneembodiment, the location idle time view 800I of the central server userinterface 800 is configured such that each statistics category headingin the idle time efficiency table 2052 is a button selectable by a user(e.g., by clicking using a mouse-controlled pointer). As such, thelocation idle time module 2000 is configured to recognize a user'sselection of any one of the table's headings. If the location idle timemodule 2000 detects a user selection, it arranges the list of driversand their associated statistical data according to the selectedstatistical category. For example, in one embodiment, the location idletime module 2000 reviews the values displayed in the column associatedwith the selected category, arranges the values numerically in orderfrom least to greatest (or greatest to least), and displays the each rowof driver statistics in order according to the values in the selectedcategory. As noted earlier, the drivers listed in the driver menu 806are each associated with the user-selected location (e.g., the locationspecified in the location pull-down menu 802). Accordingly, the locationidle time module 2000 permits a user-via the location idle time view800I of the central server user interface 800—to compare drivers from acommon location based on the various aforementioned idle time efficiencystatistics.

Location Delay Code Module

According to various embodiments, the location delay code module 2100may generally be configured for providing delay code information for auser-selected group of drivers. In one embodiment, the location delaycode module 2100 is associated with a location delay code tab 864 (shownin FIG. 35). As such, the central server 120 is configured to run thelocation delay code module 2100 in response to a user's selection of thelocation delay code tab 864.

FIG. 34 illustrates steps executed by the location delay code module2100 to generate delay code information for a group of drivers accordingto one embodiment. Beginning at step 2102, the location delay codemodule 2100 displays a location delay code view of the central serveruser interface 800. For example, FIG. 35 shows a location delay codeview 800J of the central server user interface 800 according to oneembodiment. In the illustrated embodiment, the location delay code view800J displays a delay code table 2152, which indicates some or all ofthe following for each delay code entered by the group of drivers: thedelay code's type (e.g., ED, BB), the delay code's start time (e.g.,14:32:00), the delay code's end time (e.g., 15:02:00), the total time ofthe delay code (e.g., 30 minutes), a brief description of the delay code(e.g., Lunch, Stuck in Traffic, Waiting for Door, Fueling Vehicle, TrainTracks, Waiting at Security, Waiting for Freight, Waiting for Bill ofLading), and a brief description of the location where the driver waswhen the delay code was entered (e.g., a postal address, lunch,returning to yard). In addition, the location delay code view 800Jincludes the various menus and options 802-809 and map display 810 ofthe start-up view shown in FIG. 8.

Next, at step 2104, the location delay code module 2100 identifies anddisplays the first driver associated with the user-selected location.For example, in one embodiment, the location delay code module 2100reviews the list of drivers in the driver menu 806, identifies the firstlisted driver, and displays the driver in the delay code table 2152. Thelocation delay code module 2100 then defines the identified driver asthe “current” driver for performing steps 2106-2114.

Next, at step 2106, the location delay code module 2100 retrieves thedata associated with the current driver from the loaded segmented data(e.g., the segmented data loaded by the central server 120 in step 912of FIG. 9) and stores the retrieved data (e.g., in the central server'smemory) for use in performing steps 2108-2118. As the segmented dataloaded by the central server 120 correspond to the user-selected date,the data retrieved in step 2106 will indicate the current driver's delaycodes on the user-selected date.

Next, at step 2108, the location delay code module 2100 reviews thesegmented data retrieved in step 2106 in chronological order andidentifies the first indicated delay code segment. The first identifieddelay code segment is then defined as the current delay code as thelocation delay code module 2100 performs steps 2110-2114. Next, in step2110, the location delay code module 2100 identifies and retrieves thedelay code type, start time, end time, brief description, and locationfor the current delay code from the retrieved segmented data. Thelocation delay code module 2100 then displays the retrieved type, starttime, end time, brief description, and location for the current delaycode in the appropriate cells of the delay code table 2152 as shown inFIG. 35.

Next, at step 2112, the location delay code module 2100 calculates anddisplays the total time for the current delay code. For example, in oneembodiment, the location delay code module 2100 determines the totaltime by calculating the difference between the current delay code'sstart time and finish time retrieved in step 2110. The location delaycode module 2100 then displays the calculated total time in theappropriate cell of the delay code table 2152.

Next, at step 2114, the location delay code module 2100 determineswhether there are additional delay codes in the loaded segmented data.In one embodiment, the location delay code module 2100 executes step2114 by reviewing the retrieved segmented data for delay code segmentsoccurring after the current delay code. If there is an additional delaycode segment, the location delay code module 2100 moves to step 2116where it identifies the next delay code segment and defines it as thenew current delay code. As shown in FIG. 34, the location delay codemodule 2100 will then loop back through steps 2110-2114 and perform theaforementioned steps for the new current delay code.

If there are no additional delay code segments, the location delay codemodule 2100 moves to step 2118, where it determines whether there areadditional drivers associated with the user-selected location. Forexample, in one embodiment, the location delay code module 2100 isconfigured to initially generate delay code information for variousdrivers in the order that they appear in the driver menu 806.Accordingly, in step 2118, the location delay code module 2100 reviewsthe list of drivers in the driver menu 806 and determines whether thereis at least one additional driver listed after the current driver. Ifthe location delay code module 2100 determines there are additionaldrivers associated with the user-selected location, the location delaycode module 2100 moves to step 2120. In step 2120, the location delaycode module 2100 identifies and displays the next driver listed in thedriver menu 806. As in step 2104, the location delay code module 2100reviews the list of drivers in the driver menu 806, identifies the nextlisted driver, and displays the driver in the delay code table 2152. Thelocation delay code module 2100 then defines the newly identified driveras the “current” driver. As shown in FIG. 34, the location delay codemodule 2100 then loops back and performs steps 2106-2118 for the newlyidentified current driver.

In certain embodiments, the location delay code module 2100 may befurther configured to the delay code segments shown in the delay codetable 2152 according to any of the attributes displayed in the table2152. For example, in response to a user selecting the “total time”column heading, the location delay code module 2100 will group anddisplay the identified delay code segments according to their total time(e.g., with the longest duration at the top of the table 2152).

Location Stop Exceptions Module

According to various embodiments, the location stop exception module2200 may generally be configured for providing stop statistics for auser-selected group of drivers on a user-selected date. In oneembodiment, the location stop exception module 2200 is associated with alocation stop exceptions tab 865 (shown in FIG. 37). As such, thecentral server 120 is configured to run the location stop exceptionmodule 2200 in response to a user's selection of the location stopexceptions tab 865.

FIG. 36 illustrates steps executed by the location stop exception module2200 to provide stop statistics for a user-selected group of driversaccording to one embodiment. Beginning at step 2202, the location stopexception module 2200 displays an location stop exception view of thecentral server user interface 800. For example, FIG. 37 shows a locationstop exception view 800K of the central server user interface 800according to one embodiment. In the illustrated embodiment, the locationstop exception view 800K displays a stop statistics table 2252, whichindicates some or all of the following for each stop performed by eachdriver in the user-selected group of drivers: the driver name associatedwith the stop, the stop number (e.g., 1, 2, 3), the stop type (e.g.,delivery or “DL,” pickup or “PU,” return to building or “RTB), the stopcomplete time (e.g., the time at which the stop is completed, such as22:11:00), the distance in miles from the previous stop—indicated asmiles-to-stop or “MTS” (e.g., 18.5 miles), the total time elapsed whileexecuting the stop—indicated as “Stop Time” (e.g., 10.00 minutes), thetotal time elapsed traveling from the previous stop and executing thecurrent stop—indicated as “Total Time” (e.g., 84.00 minutes), the amountof time the driver was on the property of a shipping hub during thetime-to-stop period—indicated as “On Property” (e.g., 23.63 minutes),the amount of non-travel time to stop occurring between the completionof the previous stop and the beginning of the current stop—indicated as“Non-Travel TTS” (e.g., 5.85 minutes), the amount of pure travel timeoccurring between the completion of the previous stop and the beginningof the current stop—indicated as “Pure Travel” (e.g., 45.37 minutes),the amount of lunch time occurring between the completion of theprevious stop and beginning of the current stop—indicated as “Lunch”(e.g., 30.00 minutes), and the amount of driver-coded delay timeoccurring between the completion of the previous stop and the beginningof the current stop-indicated as “Coded Delay” (e.g., 1.50 minutes).Although the Lunch and Coded Delay columns are not visible in FIG. 37, ascroll bar associated with stop statistics table 2252 allows a user tomove the display in order to view those columns.

In addition, the location stop exception view 800K includes a createreport button 2254 configured to generate a printable stop statisticsreport (e.g., a .pdf file) showing the stop statistics table 2252. Thelocation stop exception view 800K also includes the various menus andoptions 802-809 and map display 810 of the start-up view shown in FIG.8. Furthermore, the location stop exception view 800K includes a stopfilter menu 2256, which comprises a plurality of adjustable filters. Forexample, in the illustrated embodiment of FIG. 37, the stop filter menu2256 includes an on property filter, non-travel time to stop filter,coded delay filter, stop time filter, total time filter, pure travelfilter, miles to stop filter, return to building filter, and a lunchfilter. As shown, many of the filters can be adjusted according to timeor distance values that may be input by a user or selected from one ofthe drop down menus associated with each filter. As described in greaterdetail below, a user may adjust the settings of the various filters inthe filter menu 2256 to control which of the stop statistics determinedby the location stop exception module 2200 are displayed in the stopstatistics table 2252.

Next, at step 2204, the location stop exception module 2200 identifiesthe first driver associated with the user-selected location. Forexample, in one embodiment, the location stop exception module 2200reviews the list of drivers in the driver menu 806 and identifies thefirst listed driver. The location stop exception module 2200 thendefines the identified driver as the “current” driver for performingsteps 2206-2224.

Next, at step 2206, the location stop exception module 2200 retrievesdata associated with the current driver from the loaded segmented data(e.g., the segmented data loaded by the central server 120 in step 912of FIG. 9) and loaded operational data (e.g., the operational dataloaded by the central server 120 in step 906 of FIG. 9), and stores theretrieved data (e.g., in the central server's memory) for use inperforming steps 2208-2220. As the segmented data loaded by the centralserver 120 correspond to the user-selected date, the data retrieved instep 2206 will indicate stops performed by the current driver on theuser-selected date.

Next, in step 2208, the location stop exception module 2200 reviews thesegmented data retrieved in step 2206 in chronological order andidentifies the first indicated stop segment. The identified first stopsegment is then defined as the current stop as the location stopexception module 2200 performs steps 2210-2220. Next, in step 2210, thelocation stop exception module 2200 identifies and retrieves—from thesegmented data retrieved in step 2206—the stop type and stop completetime for the current stop. In addition, the location stop exceptionmodule 2200 assigns a stop number to the current stop (e.g., byassigning “1” to the first identified stop and 2, 3, 4, etc. tosuccessively identified stops).

Next, in step 2212, the location stop exception module 2200 determinesand displays the miles traveled to the current stop (e.g., “miles tostop” or “MTS). In one embodiment, the location stop exception module2200 determines the miles to stop by first reviewing the operationaldata retrieved in step 2206 and identifying telematics data thatindicates the vehicle distance traveled (e.g., the vehicle's odometerreading) and that was captured at the start of the current stop segment(e.g., when the vehicle's engine was turned off, or when the vehicle 100slowed to a stop immediately prior to the start of the stop segment). Ifthe current stop segment is the first stop, the location stop exceptionmodule 2200 stores the retrieved distance data as the miles to stop forthe first stop segment. If the current stop segment is not the firststop, the location stop exception module 2200 also identifies telematicsdata that indicates vehicle distance traveled and that was captured atthe end of the previous stop segment (e.g., when the vehicle's enginewas started, or when the vehicle 100 accelerated from standstill). Thelocation stop exception module 2200 then subtracts the vehicle distancetraveled at the end of the previous stop from the vehicle distancetraveled at the beginning of the current stop and stores the result asthe miles to stop for the current stop. In other embodiments, thelocation stop exception module 2200 may determine the miles to stop forthe current stop using the GPS-based techniques described herein.

Next, at step 2214, the location stop exception module 2200 determinesthe stop time, on property time, non-travel time to stop, pure traveltime, and total time for the current stop. In one embodiment, thelocation stop exception module 2200 determines the stop time by firstidentifying and retrieving the stop start time for the current stop fromthe loaded segmented data. The location stop exception module 2200 thencalculates the difference between the stop complete time (retrieved instep 2210) and the stop start time, and stores the result as the stoptime for the current stop.

Next, according to one embodiment, the location stop exception module2200 determines the on property time by first reviewing the retrievedsegmented data for any on property segments occurring between the stopstart time of the current stop and the stop finish time of any precedingstop. For example, where the current stop is the first stop, thelocation stop exception module 2200 will recognize the On Propertysegment occurring at the beginning of the driver's day. If an OnProperty segment is identified, the location stop exception module 2200then determines the start time and finish time for the identified OnProperty segment, and determines the On Property time—the duration ofthe On Property segment—by calculating the difference between thesegment's start time and finish time. Where multiple on propertysegments are identified between the stop start time of the current stopand the stop finish time of any preceding stop, this process is repeatedand the location stop exception module 2200 sums the duration of theidentified on property segments to determine the on property time.

Next, according to one embodiment, the location stop exception module2200 determines the non-travel time to stop by reviewing the retrievedsegmented data for any non-travel time to stop segments occurringbetween the stop start time of the current stop and the stop finish timeof any preceding stop. If a non-travel time to stop segment isidentified, the location stop exception module 2200 then determines thestart time and finish time for the identified non-travel time to stopsegment and determines the non-travel time to stop—the duration of thenon-travel time to stop segment—by calculating the difference betweenthe segment's start time and finish time. Where multiple non-travel timeto stop segments are identified between the stop start time of thecurrent stop and the stop finish time of any preceding stop, thisprocess is repeated and the location stop exception module 2200 sums theduration of the identified non-travel time to stop segments to determinethe non-travel time to stop.

Next, according to one embodiment, the location exception module 2200determines the pure travel time by reviewing the retrieved segmenteddata for any travel segments occurring between the stop start time ofthe current stop and the stop finish time of any preceding stop. If atravel segment is identified, the location exception module 2200 thendetermines the start time and finish time for the identified travelsegment and determines the pure travel time—the duration of the travelsegment—by calculating the difference between the segment's start timeand finish time. Where multiple travel segments are identified betweenthe stop start time of the current stop and the stop finish time of anypreceding stop, this process is repeated and the location exceptionmodule 2200 sums the duration of the identified travel segments todetermine the pure travel time.

Next, according to one embodiment, the location exception module 2200determines the total time for the current stop by first identifying thestop finish time of the preceding stop or, where the current stop is thefirst stop, the start time of the preceding on-property segment. Next,the location exception module 2200 determines the time to stop bycalculating the difference between the stop start time identifiedearlier and the stop finish time of the preceding stop (or start time ofthe preceding on-property segment). Next, the location exception module2200 calculates the total time for the current stop by summing thecalculated stop time and time to stop.

Next, in step 2216, the location stop exception module 2200 determinesthe lunch time and coded delay time for the current stop. In oneembodiment, the location exception module 2200 first reviews theretrieved segmented data for any lunch segments occurring between thestart time of the current stop and the finish time of a preceding stop.If a lunch segment is identified, the location exception module 2200then determines the start time and finish time for the identified lunchsegment and determines the lunch time—the duration of the lunchsegment—by calculating the difference between the segment's start timeand finish time.

The location exception module 2200 next reviews the retrieved segmenteddata for any coded delay segments occurring between the start time ofthe current stop and the finish time of any preceding stop. If a codeddelay segment is identified, the location exception module 2200 thendetermines the start time and finish time for the identified coded delaysegment and determines the coded delay time—the duration of the codeddelay segment—by calculating the difference between the segment's starttime and finish time. Where multiple coded delay segments are identifiedbetween the start time of the current stop and the finish time of apreceding stop, this process is repeated and the location exceptionmodule 2200 sums the duration of the identified coded delay segments todetermine the coded delay time.

Next, in step 2218, the location exception module 2200 determineswhether there are additional stops in the retrieved segmented data. Inone embodiment, the location exception module 2200 executes step 2218 byreviewing the retrieved segmented data for stop segments occurring afterthe current stop. If there is an additional stop segment, the locationexception module 2200 moves to step 2220 where it identifies the nextstop segment (or return to building segment) and defines the newlyidentified stop as the new “current” stop. As shown in FIG. 36, thelocation exception module 2200 will then loop back through steps2210-2218 and perform the aforementioned steps for the new current stopsegment.

If there are no additional stop segments, the location exception module2200 moves to step 2222, where it determines whether there areadditional drivers associated with the user-selected location. Forexample, in one embodiment, the location exception module 2200 isconfigured to determine stop statistics for various drivers in the orderthat they appear in the driver menu 806. Accordingly, in step 2222, thelocation exception module 2200 reviews the list of drivers in the drivermenu 806 and determines whether there is at least one additional driverlisted after the current driver. If the location exception module 2200determines there are additional drivers associated with theuser-selected location, the location exception module 2200 moves to step2224. In step 2224, the location exception module 2200 identifies thenext driver listed in the driver menu 806. The location exception module2200 then defines the newly identified driver as the “current” driver.As shown in FIG. 36, the location exception module 2200 then loops backand performs steps 2206-2222 for the newly identified current driver.

If the location exception module 2220 determines there are no additionaldrivers associated with the user-selected location, the locationexception module 2200 moves to step 2226. In step 2226, the locationexception module 2200 reviews the stop filter settings and displaysthose stop statistics determined in steps 2204-2224 that meet the stopfilter settings. For example, where the “all” filter setting isselected, the location exception module 2200 will display stopstatistics determined by the location exception module 2200 in the stopstatistics table 2252. However, if only the “stop time” filter isselected and is set to 15 minutes, the location exception module 2200will show only the stop statistics associated with driver stops having astop time of 15 minutes or greater. Likewise, multiple filter optionsmay be simultaneously checked such that a user can choose to view anycombination of stop statistics. In other embodiments, the various filtersettings may comprise percentages (e.g., a setting which filters stopstatistics but those associated with the top 10% highest total timestops). Accordingly, in accordance with the stop filter menu 2256settings, the location exception module 2200 is capable of comparingdrivers according any of the statistical categories shown in FIG. 37.

Location Safety Module

According to various embodiments, the central server 120 may furtherinclude a location safety module (not shown) configured for providingvarious safety information for a user-selected group of drivers (e.g.,associated with a particular shipping hub) over a defined period of time(e.g., a user-selected day). In one embodiment, the location safetymodule is associated with a location safety tab 866 (shown in FIG. 42).As such, the central server 120 is configured to run the location safetymodule in response to a user's selection of the location safety tab 866.

FIG. 42 shows a location safety view 800P of the central server userinterface 800 generated by the location safety module according to oneembodiment. As shown in FIG. 42, the user may select a particular groupof drivers (e.g., based on location or supervisor) or a group of driversin the top 5 of drivers in a particular statistic category. The locationsafety module then reviews operational data for the user-selected groupof drivers and determine and display—for each driver—the driver's groupnumber, vehicle number, route number, device error codes, number of seatbelt events (e.g., seat belt off while traveling, seat belt off whileengine on), seat belt distance (e.g., distance traveled during seat beltevents), number of recording in travel instances (e.g., use of themobile device 110 while traveling), total idle time, bulk head door openevents (e.g., instance where door is open or unlocked while vehicle ison or traveling), bulk head distance (e.g., distance traveled while doorwas open or unlocked), total vehicle backing events, and total backingdistance. These values are then displayed in the location safety view800P as shown in FIG. 42.

In addition, as shown in FIG. 42, the location safety moduledetermines—for the group of drivers—the total number and average numberof seat belt off events, the total and average distance traveled duringseat belt events, the total and average time recording in travel, thetotal and average time idling during delivery, the total and averagenumber of bulk head open events, the total and average distance traveledduring bulk head door events, the total and average number of backingevents, the total and average backing distance, the total and averagevehicle speed, the total and average number of harsh braking events(e.g., slowing more than 15 mph in two seconds), and the total andaverage amount of idle time.

Location Dispatch Profile Module

According to various embodiments, the location dispatch profile module2300 may generally be configured for providing dispatch profilestatistics for a user-selected driver. In one embodiment, the locationdispatch profile module 2300 is associated with a location dispatchprofile tab 866 (shown in FIG. 39). As such, the central server 120 isconfigured to run the location dispatch profile module 2300 in responseto a user's selection of the location dispatch profile tab 866.

FIG. 38 illustrates steps executed by the location dispatch profilemodule 2300 to provide dispatch profile statistics for a user-selecteddriver according to one embodiment. Beginning at step 2302, the locationdispatch profile module 2300 displays a location dispatch profile viewof the central server user interface 800. For example, FIG. 39 shows alocation dispatch profile view 800L of the central server user interface800 according to one embodiment. In the illustrated embodiment, thelocation dispatch profile view 800L displays a dispatch statistics table2352 and a delivery performance statistics table 2354. The deliveryperformance statistics table 2354 indicates statistics for a driver'sperformance during one or more particular work shifts (e.g., a full workday, a morning work shift, an afternoon work shift, multiple work days,multiple morning or afternoon work shifts, or other periods of timeduring which one or more vehicle operators are scheduled to performdelivery-related activities), including number of trips made by theselected driver, the driver's total pickup and delivery hours, thenumber of delivery stops performed by the driver, the number of pickupstops performed by the driver, the total number of stops performed bythe driver, the number of stops per hour performed by the driver, thedriver's average stop time, the number of miles traveled by the driver,the miles traveled per stop by the driver, and the total weight of itemspicked up or delivered by the driver. Similarly, the dispatch statisticstable 2352 indicates average values of the same driver performancestatistics for one or more work shifts corresponding to unique dispatchranges (e.g., ranges of total stops made by a driver on a single day).For example, the statistics shown in the “Dispatch Between 11-15 Stops”row indicate the driver's average performance in each category on daysfalling within the 11-15 stops dispatch range.

In addition, the location dispatch profile view 800L includes a profilereport menu 2356, which provides a start date menu, end date menu, anddriver menu configured to permit a user to select a particular daterange and driver to generate dispatch profile data for. As notedearlier, the profile report menu 2356 may be used in lieu of the variousmenus and options 802-809 shown in FIG. 8. In addition, the locationdispatch profile view 800L includes a create report button 2354configured to generate—in response to a user's selection—a printabledispatch profile report (e.g., a .pdf or .xls file) showing the dispatchstatistics table 2352 and delivery performance statistics table 2354.The location dispatch profile view 800L also includes the map display810 of the start-up view shown in FIG. 8.

Next, at step 2304, the location dispatch profile module 2300 identifiesthe first date in the user-selected date range (e.g., the range of datespecified by the user via the profile report menu 2356) and defines theidentified date as the “current” date. Next, at step 2306, the locationdispatch profile module 2300 retrieves data associated with the currentdate from the loaded segmented data (e.g., the segmented data loaded bythe central server 120 in step 912 of FIG. 9) and loaded operationaldata (e.g., the operational data loaded by the central server 120 instep 906 of FIG. 9), and stores the retrieved data (e.g., in the centralserver's memory) for use in performing steps 2308-2320. As the dataloaded by the central server 120 corresponds to the user-selected driver(as specified in the profile report menu 2356), the data retrieved instep 2306 will be indicative of the selected driver's activity on thecurrent date.

Next, at step 2308, the location dispatch profile module 2300 determinesand displays various delivery performance statistics for the selecteddriver on the current date. For example, in one embodiment, the locationdispatch profile module 2300 determines—based on the segmented data andoperational data retrieved in step 2306—the number of trips made by theselected driver, the driver's total pickup and delivery hours, thenumber of delivery stops performed by the driver, the number of pickupstops performed by the driver, the total number of stops performed bythe driver, the number of stops per hour performed by the driver, thedriver's average stop time, the number of miles traveled by the driver,the miles traveled per stop by the driver, and the total weight of itemspicked up or delivered by the driver. These values may each bedetermined using various methods described herein, such as thosedescribed above in relation to the location performance module 1800. Asshown in FIG. 39, the location dispatch profile module 2300 nextdisplays the determined values in the delivery performance statisticstable 2354.

Next, at step 2310, the location dispatch profile module 2300 determineswhether there are additional dates in the selected date range for whichperformance statistics have not been determined. If the locationdispatch profile module 2300 determines there is at least one additionaldate in the selected date range, the location dispatch profile module2300 moves to step 2312. In step 2312, the location dispatch profilemodule identifies the next date in the selected date range and definesthe newly identified date as the “current” date. As shown in FIG. 38,the location dispatch profile module 2300 then loops back through steps2306-2310 to determine performance statistics for the selected driver onthe new current date. If the location dispatch profile module 2300determines there are no additional dates in the selected date range, thelocation dispatch profile module 2300 moves to step 2314. At step 2314,the location dispatch profile module 2300 identifies the first dispatchrange in the dispatch statistics table 2352 (e.g., dispatch between 1-5stops) and defines the identified dispatch range as the “current”dispatch range.

Next, at step 2316, the location dispatch profile module 2300 determinesand displays delivery performance statistics for the current dispatchrange based on the statistics populated in the delivery performancestatistics table 2354. In one embodiment, the location dispatch profilemodule 2300 first identifies the dates in the selected date range onwhich the selected driver performed a total number of stops within thecurrent dispatch range. The location dispatch profile module 2300 thencounts the number of identified dates and averages each of thestatistics in the delivery performance statistics table 2354 for each ofthe identified dates. The results for each statistical category are thendisplayed in the dispatch statistics table 2352 for the current dispatchrange.

Next, at step 2318, the location dispatch profile module 2300 determineswhether there are additional dispatch ranges in the dispatch statisticstable 2352 for which performance statistics have not been determined. Ifthe location dispatch profile module 2300 determines there is at leastone additional dispatch range, the location dispatch profile module 2300moves to step 2320 where it identifies the next dispatch range in thedispatch statistics table 2352 and defines the identified dispatch rangeas the new “current” dispatch range. As shown in FIG. 38, the locationdispatch profile module 2300 then loops back through steps 2316-2318 todetermine delivery performance statistics for the new current dispatchrange. If the location dispatch profile module 2300 determines there arenot further dispatch ranges, the location dispatch profile module 2300moves to step 2322, where it monitors the location dispatch profile userinterface view 800L for a user's selection of modified profile reportmenu 2356 settings necessitating a new dispatch profile analysis.

Various User Interface Tools

According to various embodiments, the data analyzed by the variousmodules described herein may be more particularly selected by a user bydefining a geographical area on a map. For example, as shown in FIG. 43,a user may select a particular driver or group of drivers, a particulardate, and navigate to a particular portion of the user interface's mapdisplay 810 showing stops made by the selected driver or drivers. Theuser may then draw a polygon on the map and request analysis of dataassociated with the stops falling within the polygon. In response, themodule associated with the particular user interface view the user iscurrent viewing will then refine its analysis and display informationfor only those stops or travel occurring within the user-definedgeographic area.

In addition, according to various embodiments, the user may comparedifferent types of information for a driver or common information fordifferent drivers by opening multiple user interface windows. Forexample, in the illustrated embodiment of FIG. 44, the central serveruser interface 800 enables a user to run a particular type of analysisusing a particular module for a particular driver or group of drivers,and subsequently run a different analysis (e.g., using a differentdriver or different analysis type) and view the resulting informationsimultaneously in multiple windows (810A, 810B, 810C). This permits theuser to more effectively view various information generated by the fleetmanagement system 5.

Map Update Module

According to various embodiments, a map update module may also be storedon the central server 120. In such embodiments, the map update modulemay generally be configured for identifying paths traveled by a deliveryvehicle that have not been plotted or otherwise stored in the centralserver's maps and for updating the central server's maps to include theidentified paths (herein “unknown paths). The unknown paths identifiedby the map update module may include, among other things, new roads inrecently constructed residential neighborhoods, new highway off-ramps orbridges, and non-public roads or lanes in commercial areas. For example,as known methods for updating GPS-based maps are time consuming, thecentral server's maps (e.g., the above-described electronicallynavigable base map stored on the central server database) often do notinclude newly constructed roads before they are traveled by a deliveryvehicle. Similarly, as GPS-based maps often do not include non-publicroad paths, delivery vehicles frequently travel along lanes in theparking lot of a large shopping center or roads surrounding a largedistribution center that are not included in the central server's maps.

According to various embodiments, the map update module is configured toidentify unknown paths and update the central server's maps based ontelematics data captured from the delivery vehicle 100 by the telematicsdevice 102. As noted earlier herein, in various embodiments, thetelematics device 102 is configured to capture telematics data thatincludes data indicating the vehicle's location as the vehicle 100travels along a given path (e.g., GPS coordinates captured by a locationsensing device). As a result, the travel path of the vehicle 100 at anypoint during the course of an operational day can be determined andplotted on a map based on the captured telematics data (e.g., asdiscussed earlier in relation to step 908 in FIG. 9). Accordingly, themap update module is configured to identify telematics data capturedwhile the vehicle 100 is (or was) traveling along an unknown path andplot the unknown path based on the identified telematics data.

The telematics data corresponding to an unknown path can generally beidentified by determining the vehicle's distance from the nearest knownroad at the time a telematics data record is captured by the telematicsdevice 102. For example, FIG. 45 illustrates a road 3050 along which thevehicle 100 may travel. As shown in FIG. 46, the road 3050 may berepresented as a known road in the central server's maps by a string ofroad data points 3052, each of which is associated with data indicatingits respective location (e.g., GPS-compatible latitude and longitudedata). According to various embodiments, the road data points 3052 maybe positioned along the path of the road 3050 and generally spaced adistance D1 apart from one another.

FIG. 47 illustrates a plurality of location data points 3054 captured asthe vehicle 100 traveled along the road 3050. In the illustratedembodiment of FIG. 47, the distance between a particular location datapoint 3054 and the nearest road data point 3052 is indicated as thedistance D2. Although the distance between the location data points 3054themselves may vary depending on the speed of the vehicle and frequencyof the telematics data capture, each location data point 3054 isnecessarily proximate at least one of the road data points 3052. Indeed,as long as the vehicle 100 is traveling along the known road 3050, thedistance D2 between any given location data point 3054 and the nearestroad data point 3052 will not exceed the distance D1 (i.e., the distancebetween adjacent road data points 3052). Accordingly, in variousembodiments, location data points 3054 having a distance D2 from thenearest road data point 3052 that is greater than the distance D1 willcorrespond to travel along an unknown path.

For example, FIG. 48 illustrates an unknown road 3058 that extendsthrough a new residential neighborhood constructed adjacent the knownroad 3050. FIG. 49 shows a plurality of location data points 3054captured as the vehicle 100 traveled along the known road 3050, turnedfrom the known road 3050 onto the unknown road 3058, and then returnedto the known road 3050. As shown in FIG. 49, the location data points3054 captured along the unknown road 3058 have a distance D2 from theirnearest road data point 3052 that is greater than the distance D1. Assuch, the location data points 3054 corresponding to the unknown road3058 can be identified and connected to form a new path 3056representing the unknown road 3058. The location data points 3054comprising the new path 3056 can then be stored in the central server'smaps in order to update the maps to reflect the newly constructed road3058. As will be appreciated from the description herein, the processcan be used to identify and store unknown public roads, private roads,parking lot lanes, or other unknown paths traveled by the vehicle 100.

According to various embodiments, the central server 120 is configuredto run the map update module in response to a user request (e.g., arequest received via the graphical user interface 800). FIG. 51illustrates steps executed by the map update module to update thecentral servers' maps according to one embodiment. Beginning at step3002, the map update module identifies the first telematics data recordin the operational data set loaded by the central server 120 (e.g., instep 906 of FIG. 9) and defines this first data record as the “currentdata record.” Next, at step 3004, the map update module determines thevehicle's 100 distance from the nearest known road at the time of thecurrent data record's capture. In one embodiment, the map update moduleexecutes step 3004 by determining the location of the vehicle at thetime the current data record was captured (e.g., based on a locationdata point in the current data record), identifies the nearest point ona known road in relation to the vehicle's location (e.g., based on thelocation data associated with the road data points in the centralserver's maps), and calculates the distance between the vehicle'slocation and the nearest road data point.

Next, at step 3006, the map update module determines whether thedistance calculated in step 3004 exceeds a predefined threshold distance(e.g., the average distance D1 between road data points in the centralserver's maps). If the distance calculated in step 3004 does not exceedthe predefined threshold, the map update module moves to step 3010. Ifthe distance calculated in step 3004 does exceed the predefinedthreshold, the map update module moves to step 3008, where it flags thecurrent data record as a “new path point” (e.g., by associating thecurrent data record with metadata indicating it is a new path point).

Next, at step 3010, the map update module determines whether there areadditional telematics data records in the operational data set loaded bythe central server 120. If there are additional telematics data records,the map update module moves to step 3012, where it identifies the nexttelematics data record, stores it as the current data record, andrepeats steps 3004-3010. If there are no additional telematics datarecords, the map update module moves to step 3014, where it identifiesstrings of consecutive new path points (e.g., the telematics datarecords flagged as such) and stores the string of new path points as anew known path in the central server's maps.

According to various embodiments, the map update module may be furtherconfigured to permit a user to name, format, or otherwise modify newknown paths identified by the map update module. For example, in certainembodiments, the map update module may be configured to display one ormore new known paths on a current map (e.g., in the user interface's mapdisplay 810) and enable a user to designate a particular new known pathas a private road, public road, parking lot lane, or other path type(e.g., by visually comparing an identified new known path to itssurroundings on the map). The map update module may then be configuredto store the new known path as the designated path type in the centralserver's maps.

In other embodiments, the map update module may be configured toautomatically identify new known paths as being a public road, privateroad, parking lot lane, or other path type. For example, in certainembodiments, the map update module may be configured to compare thelocation of a new known path (e.g., based on GPS data associated withidentified new path points) with a plurality of predefined geo-fencedareas. In such an embodiment, the map update module may be configured todesignate new known paths identified as being located within ageo-fenced area associated with a shopping center as a privatecommercial lane (e.g., a parking lot lane or delivery lane). Likewise,the map update module may be configured to designate new known pathsidentified as being located within a residential neighborhood as a newneighborhood road, which may be public or private depending on theneighborhood. Furthermore, the map update module may be configured todesignate new known paths identified as being located within a publicarea (e.g., adjacent a highway) as being a public road. In addition, themap update module may be configured to designate any new known path as apublic road based on a default setting (e.g., such that any new knownpath is automatically designated a public road unless it is determinedto be within a private geofenced area).

In other embodiments, steps 3004-3008 of FIG. 51 may be accomplished bythe telematics device 102. For example, as noted earlier herein, thetelematics device 102 may be configured to recognize vehicle eventscharacterized by data generated by GPS-sensors or other location sensingdevices, such as a vehicle traveling onto a known road (e.g., a roadrecognized by a GPS device) and a vehicle traveling off of a known road(e.g., exceeding a certain predefined distance from a known road). Assuch, the telematics device 102 may be configured to automatically flagtelematics data records as new path points at the time they arecaptured. Likewise, the map update module may be configured to identifytelematics data records flagged by the telematics device 102 and executesteps 3002 and 3010-3014 accordingly.

Off-Course Travel Module

According to various embodiments, an off-course travel module may alsobe stored on the central server 120. In such embodiments, the off-coursetravel module may generally be configured for comparing the travel pathof one or more vehicles with at least one planned travel path in orderto identify portions of the vehicle travel path that are off-course fromthe planned travel path. After identifying off-course portions of avehicle's travel path, the off-course travel module may be furtherconfigured to generate a graphical display indicating the off-courseportions of the vehicle's travel path on a geographical map. Inaddition, the off-course travel module may be configured to determineone or more statistics relating to the off-course portion of thevehicle's travel path. In various embodiments, the off-course travelmodule may be configured to accomplish these tasks using techniquesanalogous to those described above in relation to the map update module.

According to various embodiments, the central server 120 is configuredto run the off-course travel module in response to a user request (e.g.,a request received via the graphical user interface 800). As discussedearlier herein, user input received via the user interface 800 mayspecify one or more particular drivers, one or more particular vehicles,one or more particular time periods, and/or a particular geographicalarea. Accordingly, the off-course travel module may be configured tofirst retrieve planning data indicating a predefined planned route forthe user-selected driver or vehicle (e.g., a planned delivery route forthe user-specified driver during the user-specified time period). Thisplanning data may be retrieved, for example, from the aforementionedPlanning Data Set stored on the central server database. In variousembodiments, the planning data defining the planned route may comprise astring of road data points, each of which is associated with dataindicating its respective location (e.g., GPS-compatible latitude andlongitude data). According to various embodiments, the road data pointsmay be positioned along the vehicle's planned path and generally spaceda fixed distance apart from one another.

Next, the off-course travel module compares the user-selected vehicle'stravel path to the vehicle's planned route. As noted earlier herein, invarious embodiments, the telematics device 102 is configured to capturetelematics data that includes data indicating the vehicle's location asthe vehicle 100 travels along a given path (e.g., GPS coordinatescaptured by a location sensing device). As a result, the travel path ofthe vehicle 100 at any point during the course of an operational day canbe determined and plotted on a map based on the captured telematics data(e.g., as discussed earlier in relation to step 908 in FIG. 9).Accordingly, off-course portions of the vehicle's travel path can beidentified by determining the vehicle's distance from the nearest pointon the planned route at the time a particular telematics data record iscaptured by the vehicle's telematics device 102 and identifying thosetelematics data records captured from an off-course location. Byidentifying strings of off-course telematics data records, theoff-course travel module can identifying off-course portions of thevehicle's travel path.

For example, in one embodiment, the off-course travel module identifiesthe first telematics data record in the operational data set loaded bythe central server 120 (e.g., in step 906 of FIG. 9) and defines thisfirst data record as the “current data record.” Next, the off-coursetravel module determines the vehicle's 100 distance from the nearestpoint on the planned route at the time of the current data record'scapture. In one embodiment, the off-course travel module accomplishesthis by determining the location of the vehicle at the time the currentdata record was captured (e.g., based on a location data point in thecurrent data record), identifying the nearest point on the planned routein relation to the vehicle's location (e.g., based on the location dataassociated with the road data points in the central server's maps), andcalculating the distance from the vehicle's location to the nearestpoint on the planned route.

Next, the off-course travel module determines whether the distancecalculated in exceeds a predefined threshold distance (e.g., 50 feetfrom the nearest point on the planned route). If the distance calculatedexceeds the predefined threshold, the off-course travel module flags thecurrent data record as an “off-course path point” (e.g., by associatingthe current data record with metadata indicating it is an off-coursepath point). If the distance calculated does not exceed the predefinedthreshold, the off-course travel module does not mark the current datarecord as an off-course path point.

Next, the off-course travel module determines whether there areadditional telematics data records in the operational data set loaded bythe central server 120. If there are additional telematics data records,the off-course travel module identifies the next telematics data record,stores it as the current data record, and repeats the aforementionedsteps to determine whether the current data record represents anoff-course path point. If there are no additional telematics datarecords, off-course travel module identifies strings of consecutiveoff-course path points (e.g., the telematics data records flagged assuch) and stores the string of off-course path points as an off-courseportion of the vehicle's travel path. In various embodiments, theabove-described process or identifying off-course portions of a vehicletravel path may be repeated to identifying off-course portions of travelpaths associated with additional vehicles or drivers as requested by auser.

In other embodiments, aforementioned steps performed by the off-coursetravel module may the accomplished by the telematics device 102. Forexample, as noted earlier herein, the telematics device 102 may beconfigured to recognize vehicle events characterized by data generatedby GPS-sensors or other location sensing devices, such as a vehicletraveling onto a planned path (e.g., a planned path associated with adriver operating the vehicle) and a vehicle traveling off of a plannedpath (e.g., exceeding a certain predefined distance from a plannedpath). As such, the telematics device 102 may be configured toautomatically flag telematics data records as off-course path points atthe time they are captured. Likewise, the off-course travel module maybe configured to identify telematics data records flagged by thetelematics device 102 and execute the aforementioned steps accordingly.

After identifying one or more off-course portions of a particularvehicle's travel path, the off-course travel module may be furtherconfigured to generate a graphical display indicating the off-courseportions of the vehicle's travel path on a geographical map. Forexample, in one embodiment, the off-course travel module may beconfigured to highlight off-course portions of one or more vehicle pathsshown in the user interface's map display 810 (e.g., by showing theoff-course portions in a different color from the on-course portions ofthe vehicle travel path). In certain embodiments, the vehicle's travelpath may be shown in combination with the planned route (e.g., byoverlaying the actual travel path over the planned route).

In addition, the off-course travel module may be configured to determineone or more statistics relating to the off-course portion of thevehicle's travel path. For example, in one embodiment, the off-coursetravel module may be configured for determining—based on telematics dataand/or service data associated with the off-course portion of thevehicle path—the duration of the off-course portion of the vehicletravel path, the distance traveled during the off-course portion of thevehicle travel path, any vehicle activity segments occurring during theoff-course portions of the vehicle travel path (e.g., lunch segments,travel delay segments, non-travel time to stop segments, etc.). Inaccordance with user preferences, these statistics may be determined anddisplayed in relation to individual off-course portions of a vehicletravel path or cumulatively for all off-course vehicle travel pathportions for a particular vehicle or driver during a certain period oftime.

Travel Delay Determining Module

According to various embodiments, a travel delay determining module mayalso be stored on the central server 120. In such embodiments, thetravel delay determining module may generally be configured fordetermining and/or forecasting travel delays (e.g., travel delayinformation) for streets, street segments, geographic areas (includinguser-selected geographic areas), geofenced areas (including user-definedgeofenced areas), and/or the like based on real-time telematics dataand/or historical telematics data (which may include images and/or imagedata).

According to various embodiments, the central server 120 can beconfigured to run the travel delay determining module regularly,periodically, continuously, and/or in response to certain triggers suchas a user request (e.g., a request received via the graphical userinterface 800). In one embodiment, the user may select one or moregeographical areas using the map drawing tool shown in FIG. 43 anddescribed above (e.g., by drawing a polygon in the map display area ofthe user interface), or using other methods described herein (e.g.,selecting a predefined work area, delivery route, or other geographicalarea). In another embodiment, the central server 120 can be configuredto determine and/or forecast travel delays for all street segments, allstreet segments in a geographic or geofenced area, in specificallyidentified geographic or geofenced areas, and/or the like regularly,periodically, continuously, and/or in response to certain triggers. Inanother embodiment, the central server 120 can be configured to run thespeed determining module in response to a request received from amapping-based website/server. In one example, a request may be receivedvia the mapping-based website/server from a user desiring to travel frompoint A (1201 Peachtree Street Northeast, Atlanta, Ga. 30309) to point B(4199 Paces Ferry Road SE, Atlanta, Ga. 30339).

Additionally, travel delays for streets, street segments, geographicareas, geofenced areas, and/or the like may correspond to specific days(e.g., weekdays, weekends, holidays, etc.) and/or specific time periods.For example, the user may specify—via one or more user interface menusor input fields—a range of recent dates to determine and/or forecasttravel delays based on telematics data captured during these dates. Thismay be useful, for example, where recent construction has changedtraffic characteristics in the selected area such that telematics datacaptured outside of a certain date range would be not be reflective ofpresent conditions. In addition, or alternatively, the user may specifya time of day, day of the week, holiday, and/or the like to determineand/or forecast travel delays based on telematics data captured during aparticular time of day. For example, the user may specify—via one ormore user interface menus or input fields—a particular time of day, suchas morning (e.g., 6 AM-10 AM), mid-day (e.g., 10 AM-2 PM), afternoon(e.g., 2 PM-5 PM), rush-hour (e.g., 5 PM-7 PM), evening (e.g., 7 PM-12AM), or night (e.g., 12 AM-6 AM). In various embodiments, the traveldelay determining module may have one or more default values associatedwith these criteria (e.g., all drivers and vehicles, operating hoursfrom 8 AM-6 PM, and data captured during the past year). Further, thetravel delays for particular times of day may correspond to specificdays, such as (1) Holidays: morning (e.g., 6 AM-10 AM), mid-day (e.g.,10 AM-2 PM), afternoon (e.g., 2 PM-5 PM), rush-hour (e.g., 5 PM-7 PM),evening (e.g., 7 PM-12 AM), or night (e.g., 12 AM-6 AM); (2)Mondays-Thursdays: morning (e.g., 6 AM-10 AM), mid-day (e.g., 10 AM-2PM), afternoon (e.g., 2 PM-5 PM), rush-hour (e.g., 5 PM-7 PM), evening(e.g., 7 PM-12 AM), or night (e.g., 12 AM-6 AM); (3) Fridays: morning(e.g., 6 AM-10 AM), mid-day (e.g., 10 AM-2 PM), afternoon (e.g., 2 PM-5PM), rush-hour (e.g., 5 PM-7 PM), evening (e.g., 7 PM-12 AM), or night(e.g., 12 AM-6 AM); (4) Saturdays and Sundays: morning (e.g., 6 AM-10AM), mid-day (e.g., 10 AM-2 PM), afternoon (e.g., 2 PM-5 PM), rush-hour(e.g., 5 PM-7 PM), evening (e.g., 7 PM-12 AM), or night (e.g., 12 AM-6AM).

In one embodiment, to calculate travel delays for streets, streetsegments, geographic areas, geofenced areas, and/or the like, the traveldelay determining module may be configured to first retrieve telematicsdata relating to the same (which may include images and/or image data).For example, in one embodiment, the travel delay determining module maybe configured to retrieve telematics data and segmented data associatedwith specific streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria from the central server databaseusing the methods described herein. In various embodiments, the traveldelay determining module may be configured to retrieve all dataassociated with the specific streets, street segments, geographic areas,geofenced areas, and/or user-specified criteria (e.g., all storedtelematics data for any vehicle that was captured corresponding to thesame and during a specified time period) or a sample set of dataassociated with the specific streets, street segments, geographic areas,geofenced areas, and/or user-specified criteria (e.g., stored data for100 random vehicles that was captured corresponding to the same andduring a specified time period). In further embodiments, the traveldelay determining module may be configured to retrieve data for specificdrivers or vehicles, as well as data for all drivers and/or vehiclesassociated with a particular entity, organization, shipping hub,distribution center, vehicle make or model, fitting within a particulardemographic, and/or the like.

Next, the travel delay determining module can identify all travel delaysegments in the retrieved segmented data (which may be based imagesand/or image data of the vehicle 100 in a stationary position). Asdiscussed herein, travel delay segments identified by the datasegmenting module 1000 may each represent a period of engine idle timeoccurring during a Travel segment (e.g., when a vehicle is stopped at anintersection, stopped in heavy traffic, or for some other reason). Next,the travel delay determining module can sum the duration of allidentified travel delay segments to determine the total amount of traveldelay time indicated by the retrieved data for the correspondingstreets, street segments, geographic areas, geofenced areas, and/oruser-specified criteria.

Next, the travel delay determining module can determine the total amountof miles traveled by all vehicles represented in the retrieved datacorresponding to the streets, street segments, geographic areas,geofenced areas, and/or user-specified criteria. In other words, thetotal amount of miles traveled by vehicles associated with the retrieveddata during the specified time period. For example, if the dataretrieved by the travel delay determining module corresponds to only onevehicle, the travel delay module will determine the total distancetraveled by that vehicle represented in the retrieved data correspondingto the streets, street segments, geographic areas, geofenced areas,and/or user-specified criteria. Likewise, if the data retrieved by thetravel delay determining module corresponds to multiple vehicles, thetravel delay module will determine the total distance traveled by all ofthose vehicles represented in the retrieved data corresponding to thestreets, street segments, geographic areas, geofenced areas, and/oruser-specified criteria. This total distance traveled value may bedetermined based on the retrieved telematics data (e.g., based onodometer readings, hubometer readings, GPS position, and/or the like).In other embodiments, the total distance traveled may be determinedbased on driver-reported values retrieved by the travel delaydetermining module.

Next, the travel delay determining module determines a value indicativeof the average amount of travel delay time, for example, per unit ofdistance for the streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria and the specified time period. Forexample, in one embodiment, the travel delay determining module isconfigured to determine the average travel delays per mile (e.g., traveldelay seconds or minutes per mile). In such embodiments, the traveldelay determining module can determine this value by dividing thecalculated total amount of travel delay time by the calculated totaldistance traveled (represented in the retrieved data corresponding tothe streets, street segments, geographic areas, geofenced areas, and/oruser-specified criteria) and storing this value as the travel delays permile for the corresponding streets, street segments, geographic areas,geofenced areas, and/or user-specified criteria. In other embodiments,the travel delay determining module can determine a travel delay timevalue by dividing the calculated total distance traveled by thecalculated total amount of travel delay time (e.g., miles traveled pertravel delay minute) for the corresponding streets, street segments,geographic areas, geofenced areas, and/or user-specified criteria.

In one embodiment, the central server 120 can then assign (or store inassociation with) the determined travel delay to the correspondingstreets, street segments, geographic areas, geofenced areas, and/oruser-specified criteria. For example, in one embodiment, each street,street segment, geographic area, geofenced area, and/or user-specifiedcriteria may have a corresponding unique identifier to which thedetermined travel delays can be assigned to (or stored in associationwith) the corresponding streets, street segments, geographic areas,geofenced areas, and/or user-specified criteria. FIG. 52 shows thetravel delays assigned to street segment 1258JDQ8OI77 and thecorresponding days and time periods. The travel delays may be stored asa value indicative of the average amount of travel delay time per unitof distance associated with the corresponding streets, street segments,geographic areas, geofenced areas, and/or user-specified criteria. Aswill be recognized, a variety of records can be used to storeinformation for streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria (see FIG. 52).

Although not shown in the figures, the below table provides exemplarytravel delays for the referenced streets, street segments, geographicareas, geofenced areas, and/or user-specified criteria. The tableincludes the travel delays in terms of hours of travel delays per GPSmile and seconds of travel delays per GPS mile for traveling from pointA (1201 Peachtree Street Northeast, Atlanta, Ga. 30309) to point B (4199Paces Ferry Road SE, Atlanta, Ga. 30339).

Travel Delays Hours Seconds 1201 Peachtree Street NE, Atlanta, GA.0.0097 2.16 14th Street NE, Atlanta, GA. 0.0125 18 Williams Street NW,Atlanta, GA. 0.0056 3.96 I-75 N, Atlanta, GA. 0.0014 31.68 Exit 256 onI-75 N, Atlanta, GA. 0.0047 3.24 Mount Paran Road NW, Atlanta, GA.0.0069 20.16 Paces Ferry Road NW, Atlanta, GA. 0.0103 40.68

Further, in one embodiment, the central server 120 can be configured toautomatically generate geofenced areas corresponding to specific traveldelays, see FIG. 54. For example, the central server 120 canautomatically create a geofence around connecting or clustered streetsegments that are within a particular range, such 0-15 seconds of traveldelays per mile, 16-35 seconds of travel delays per mile, 36-50 secondsof travel delays per mile, 51-70 seconds of travel delays per mile,71-95 seconds of travel delays per mile, and/or the like. Thisessentially creates a heat map or carbon footprint map based on traveldelays. In another embodiment, the central server 120 may alsoautomatically generate geofences with and store the corresponding traveldelays for zip codes, area codes, cities, towns, counties, states,and/or the like, such as shown in FIG. 54. In this figure, eachgeofenced area may be assigned a specific amount of travel delay timeper mile, for example. The delineation can be automatically determinedby the central server 120 based on changes in travel delays over orunder a given thresholds for the street segments. As will be recognized,a variety of other approaches and techniques can be used to adapt tovarious needs and circumstances.

In further embodiments, the travel delay determining module may also beconfigured for estimating a total amount of planned idle time for avehicle within a particular geofenced area and/or geographic area. Insuch embodiments, the travel delay determining module first identifiesall start of trip segments and end of trip segments in the retrievedsegmented data. As discussed herein, start of trip segments identifiedby the data segmenting module 1000 each represent a period of engineidle time beginning with a vehicle's engine being turned on and idling,and ending when the vehicle next begins to move and the engine stopsidling. Similarly, end of trip segments identified by the datasegmenting module 1000 each represent a period of engine idle timebeginning when a vehicle stops and idles, and ending when the vehicle'sengine is next turned off. Next, the travel delay determining moduledetermines the average duration of all identified start of trip segmentsand the average duration of all identified end of trip segments. Thesevalues are then stored as the start of trip event plan time and end oftrip event plan time, respectively.

To determine the total planned idle time for a given vehicle within thestreets, street segments, geographic areas, geofenced areas, and/oruser-specified criteria, the travel delay determining module sets thenumber of planned stops received via user input as both the number ofplanned start of trip events and the number of planned end of tripevents. Finally, based on the earlier calculated travel delays per milevalue for the streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria and the aforementioned parameters,the travel delay determining module determines the total planned idletime for the vehicle by performing the following calculation:

SE=Number of Planned Start of Trip Events

SEPT=Start of Trip Event Plan Time

EE=Number of Planned End of Trip Events

EEPT=End of Trip Event Plan Time

TDPM=Travel delays Per Mile

MT=Miles TraveledTotal Planned Idle Time=(SE×SEPT)+(EE×EEPT)+(TDPM×MT)

According to various embodiments, the travel delay determining modulemay also be configured for generating a graphical representation ofthese calculated values and for providing an interactive user interfaceconfigured to enable a user to modify the various parameters noted aboveand perform multiple calculations.

Speed Determining Module

According to various embodiments, a speed determining module may bestored on the central server 120. In one embodiment, the speeddetermining module may be generally configured for determining and/orforecasting estimated speeds (without taking into account travel delays)for streets, street segments, geographic areas (including user-selectedgeographic areas), geofenced areas (including user-defined geofencedareas), and/or the like. In one embodiment, such determinations of speedinformation/data may correspond to current speeds based on telematicsdata, historical speeds based on telematics data, posted speed limits,and/or the like.

According to various embodiments, the central server 120 can beconfigured to run the speed determining module regularly, periodically,continuously, and/or in response to certain triggers such as in responseto a request originating from a mapping-based website/server (e.g.,maps.google.com, bing.com/maps/, mapquest.com, and/or the like). Forexample, a request may originate from a mapping-based website/serverthat received input via a user interface, such as the user interfaceshown in FIG. 55. In one embodiment, via the mapping-basedwebsite/server, a user may request routing directions (comprisingdistance data/information), speed estimates, or travel time estimatesfor traveling to one or more locations, request routing directions(comprising distance data/information) or time estimates for part or allof a delivery route, and/or the like. The mapping-based website/servermay in turn pass the request to the central server 120 or retrievecorresponding information already received from and/or determined by thecentral server 120. The mapping-based website/server or the centralserver 120 (or another computing entity) may also be configured todetermine routing directions (comprising distance data/information) inresponse to such requests. In another example, the request may be to thecentral server 120 from a scheduling algorithm that is scheduling adriver of a vehicle (e.g., a fleet of delivery vehicles operated by ashipping entity, a fleet of taxis or buses operated by a private orpublic transportation entity) or from a route optimization algorithmrequesting times associated with specific streets, street segments,geofenced areas, geographic areas, and/or the like in generatingdelivery routes for delivery drivers.

Regularly, periodically, continuously, and/or in response to suchtriggers or requests, the central server 120 can determine or retrievethe current estimated speeds, historical speeds, posted speed limits,and/or the like for specific street segments, geofenced areas,geographic areas, user-specified criteria, and/or the like.Additionally, based on such determinations, current estimated speeds,historical speeds, posted speed limits, for example, can be assigned to(or stored in association with) the corresponding streets, streetsegments, geographic areas, geofenced areas, and/or user-specifiedcriteria. For example, FIG. 53 shows the travel delays, posted speedlimits, and average historical speeds assigned to (or stored inassociation with) street segment 1258JDQ8OI77—along with thecorresponding days and time periods for each. In one embodiment, theposted speed limits may be collected from a variety of sources includinggovernment entities. The average speed (e.g., historical speed orcurrent speed) can be collected and determined from collected telematicsdata. As described, such average speeds can exclude data associated witha GPS signal loss. Such information can be used for determining timeestimates (which may include current estimated speeds and/or historicalspeeds) for routing directions (comprising distance data/information) orroutes and/or current estimated speeds or historical speeds for specificstreets, street segments, geofenced areas, geographic areas,user-specified criteria, and/or the like.

As previously noted, the central server 120 can be configured to run thespeed determining module in response to a request received from amapping-based website, for example. Or, the central server 120 can beconfigured to run the speed determining module regularly, periodically,or continuously and provide the current estimated speeds, historicalspeeds, posted speed limits, and/or the like to the mapping-basedwebsite/server to update the mapping-based website's/server's localfiles, for example. In one example, a request may be received via themapping-based website/server from a user desiring to travel from point A(1201 Peachtree Street Northeast, Atlanta, Ga. 30309) to point B (4199Paces Ferry Road SE, Atlanta, Ga. 30339). In this example, themapping-based website/server can initiate a request to the centralserver 120 or access locally-stored information previously received fromand/or determined by the central server 120 corresponding to currentestimated speeds, historical speeds, and/or posted speed limits for thesame. In another example, the request may be to the central server 120from a scheduling algorithm that is scheduling a driver of a vehicle(e.g., a fleet of delivery vehicles operated by a shipping entity, afleet of taxis or buses operated by a private or public transportationentity) to travel to multiple points along a route, such as from pointA, to point B, to point C, to point D, to point E, and back to point A.In yet another example, the request may be to the central server 120from a route optimization algorithm (e.g., for a transportation andlogistics company) requesting times associated with specific streetsegments, geofenced areas, geographic areas, and/or the like ingenerating delivery routes for delivery drivers. As will be recognized,a variety of other approaches and techniques can be used to adapt tovarious needs and circumstances. In response to such requests ortriggers, periodically, regularly, and/or continuously, themapping-based website/server and/or the central server 120 (or otherappropriate computing entity) can determine or retrieve the currentestimated speeds, historical speeds, posted speed limits, and/or thelike for the streets, street segments, geographic areas (includinguser-selected geographic areas), geofenced areas (including user-definedgeofenced areas), and/or the like.

Continuing with the above example, if a user requests information abouttraveling from point A (1201 Peachtree Street Northeast, Atlanta, Ga.30309) to point B (4199 Paces Ferry Road SE, Atlanta, Ga. 30339) from amapping-based website/server, the mapping-based website/server or thecentral server 120 can determine or retrieve routing directions(comprising distance data/information), current estimated speeds,historical speeds, and/or posted speed limits for the street segmentsthat will be traversed during the travel from point A (1201 PeachtreeStreet Northeast, Atlanta, Ga. 30309) to point B (4199 Paces Ferry RoadSE, Atlanta, Ga. 30339). For instance, to travel from point A (1201Peachtree Street Northeast, Atlanta, Ga. 30309) to point B (4199 PacesFerry Road SE, Atlanta, Ga. 30339), the following may be a route forcompleting the travel (shown in FIG. 56).

-   -   Step 1: 1201 Peachtree Street NE, Atlanta, Ga. 30361 traveling        0.0602 miles (381 feet) to 14th Street NE.    -   Step 2: Take the 1st right onto 14th Street NE traveling 0.4        miles to Williams Street NW.    -   Step 3: Turn right onto Williams Street NW traveling 0.2 miles        to 1-75 ramp N.    -   Step 4: Take the ramp on the left onto 1-75 N traveling 6.3        miles to exit 256.    -   Step 5: Take exit 256 toward US-41 traveling 0.2 miles to Mount        Paran Road NW.    -   Step 6: Turn left onto Mount Paran Road NW traveling 0.8 miles        to Paces Ferry Road. NW.    -   Step 7: Turn right onto Paces Ferry Road NW traveling 1.1 miles        to destination (4199 Paces Ferry Road SE, Atlanta, Ga. 30339).

With the route determined and/or the specific streets, street segments,geofenced areas, geographic areas, user-specified criteria, and/or thelike identified, the mapping-based website/server or the central server120 can determine or retrieve the current estimated speeds, historicalspeeds, and/or posted speed limits for the same corresponding to thisroute. To do so, in one embodiment, the speed determining module may beconfigured to retrieve telematics data and segmented data associatedwith specific streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria from the central server databasecorresponding to the route for completing the travel. In variousembodiments, the speed determining module may be configured to retrieveall data associated with the specific streets, street segments,geographic areas, geofenced areas, and/or user-specified criteria (e.g.,all stored telematics data for any vehicle that was capturedcorresponding to the same and during a specified time period) or asample set of data associated with the specific streets, streetsegments, geographic areas, geofenced areas, and/or user-specifiedcriteria (e.g., stored data for 100 random vehicles that was capturedcorresponding to the same and during a specified time period). In oneembodiment, the mapping-based website/server or the central server 120can either identify in or determine from the current speeds based ontelematics data, historical speeds based on telematics data, postedspeed limits, and/or the like. This may include determining the averagespeed of one or more vehicles (without taking into account traveldelays), for example, but excluding data from calculations during GPSsignal loss. Such determinations may include or exclude outlier datathat meets or exceeds a configurable threshold or the fastest andslowest speeds. The determined or retrieved speed information may bestored as a value indicative of the corresponding speed associated withthe corresponding streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria. In another embodiment, themapping-based website/server or the central server 120 can simply accessthe records to the corresponding street segments, for example, toretrieve the previously determined and stored speed information/data,such as shown in FIG. 53.

Continuing with the above example, the mapping-based website/server orthe central server 120 can determine or retrieve current estimatedspeeds, historical speeds, and/or posted speed limits for the streetsegments that will be traversed during the travel from point A (1201Peachtree Street Northeast, Atlanta, Ga. 30309) to point B (4199 PacesFerry Road SE, Atlanta, Ga. 30339). Exemplary speeds are provided in thebelow table and in Fig.

Speed Limit Historical 1201 Peachtree Street NE, Atlanta, GA. 35 31 14thStreet NE, Atlanta, GA. 45 28 Williams Street NW, Atlanta, GA. 35 15I-75 N, Atlanta, GA. 65 64 Exit 256 on I-75 N, Atlanta, GA. 25 23 MountParan Road NW, Atlanta, GA. 35 30 Paces Ferry Road NW, Atlanta, GA. 3529

Further, as shown in FIG. 53, the historical speeds and/or posted speedlimits (without taking into account travel delays) may correspond to aparticular time of day, such as morning (e.g., 6 AM-10 AM), mid-day(e.g., 10 AM-2 PM), afternoon (e.g., 2 PM-5 PM), rush-hour (e.g., 5 PM-7PM), evening (e.g., 7 PM-12 AM), or night (e.g., 12 AM-6 AM). Further,as shown in FIG. 53, the historical speeds and/or posted speed limitsmay correspond to specific days, such as (1) Holidays: morning (e.g., 6AM-10 AM), mid-day (e.g., 10 AM-2 PM), afternoon (e.g., 2 PM-5 PM),rush-hour (e.g., 5 PM-7 PM), evening (e.g., 7 PM-12 AM), or night (e.g.,12 AM-6 AM); (2) Mondays-Thursdays: morning (e.g., 6 AM-10 AM), mid-day(e.g., 10 AM-2 PM), afternoon (e.g., 2 PM-5 PM), rush-hour (e.g., 5 PM-7PM), evening (e.g., 7 PM-12 AM), or night (e.g., 12 AM-6 AM); (3)Fridays: morning (e.g., 6 AM-10 AM), mid-day (e.g., 10 AM-2 PM),afternoon (e.g., 2 PM-5 PM), rush-hour (e.g., 5 PM-7 PM), evening (e.g.,7 PM-12 AM), or night (e.g., 12 AM-6 AM); (4) Saturdays and Sundays:morning (e.g., 6 AM-10 AM), mid-day (e.g., 10 AM-2 PM), afternoon (e.g.,2 PM-5 PM), rush-hour (e.g., 5 PM-7 PM), evening (e.g., 7 PM-12 AM), ornight (e.g., 12 AM-6 AM).

With the current speeds, historical speeds, and/or posted speed limitsretrieved and/or determined, the mapping-based website/server or thecentral server 120 (or other appropriate computing entity) can use thespeed information/data to determine corresponding travel times, with orwithout travel delays.

Travel Time Determining Module

According to various embodiments, a travel time determining module maybe stored on the central server 120. In one embodiment, the travel timedetermining module may be generally configured for determining and/orforecasting travel time for streets, street segments, geographic areas(including user-selected geographic areas), geofenced areas (includinguser-defined geofenced areas), and/or the like. In one embodiment, suchdeterminations may correspond to speed information/data (e.g., currentspeeds based on telematics data, historical speeds based on telematicsdata, posted speed limits, and/or the like) and/or travel delays. Asnoted, such speeds and travel delays can be determined regularly,periodically, continuously, and/or in response to certain triggers.

According to various embodiments, the central server 120 can beconfigured to run the travel time determining module regularly,periodically, continuously, and/or in response to certain triggers suchas in response to a speed being determined or retrieved, a travel delaybeing determined or retrieved, a request originating from amapping-based website/server (e.g., maps.google.com, bing.com/maps/,mapquest.com, and/or the like), and/or the like. For example, a requestmay originate from a mapping-based website/server that received inputvia a user interface, such as the user interface shown in FIG. 55. Inone embodiment, via the mapping-based website/server, a user may requestrouting directions (comprising distance data/information), speedestimates, and/or travel time estimates for traveling to one or morelocations. The mapping-based website/server may in turn pass the requestto the central server 120 or retrieve corresponding information alreadyreceived from and/or determined by the central server 120. As previouslynoted, the mapping-based website/server or the central server 120 (oranother computing entity) may also be configured to determine routingdirections (comprising distance data/information) in response to suchrequests. Similarly, the request may be to the central server 120 from ascheduling algorithm that is scheduling a driver of a vehicle (e.g., afleet of delivery vehicles operated by a shipping entity, a fleet oftaxis or buses operated by a private or public transportation entity) orfrom a route optimization algorithm requesting times associated withspecific streets, street segments, geofenced areas, geographic areas,and/or the like in generating delivery routes for delivery drivers.

Regularly, periodically, continuously, and/or in response to suchtriggers or requests, the central server 120 can determine or retrievethe estimated travel times for specific street segments, geofencedareas, geographic areas, user-specified criteria, and/or the like.Additionally, based on such determinations, estimated travel times, forexample, can be assigned to (or stored in association with) thecorresponding streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria. For example, as described, arequest may be received via the mapping-based website/server from a userdesiring to travel from point A (1201 Peachtree Street Northeast,Atlanta, Ga. 30309) to point B (4199 Paces Ferry Road SE, Atlanta, Ga.30339). In this example, the mapping-based website/server can initiate arequest to the central server 120 or access locally-stored informationpreviously received from and/or determined by the central server 120corresponding to current estimated speeds, historical speeds, and/orposted speed limits for the same and/or travel delays. Similarly, therequest may be to the central server 120 from a scheduling algorithmthat is scheduling a driver of a vehicle (e.g., a fleet of deliveryvehicles operated by a shipping entity, a fleet of taxis or busesoperated by a private or public transportation entity) to travel tomultiple points along a route, such as from point A, to point B, topoint C, to point D, to point E, and back to point A. In yet anotherexample, the request may be to the central server 120 from a routeoptimization algorithm (e.g., for a transportation and logisticscompany) requesting times associated with specific street segments,geofenced areas, geographic areas, and/or the like in generatingdelivery routes for delivery drivers. As will be recognized, a varietyof other approaches and techniques can be used to adapt to various needsand circumstances. In response to such requests or triggers,periodically, regularly, and/or continuously, the mapping-basedwebsite/server and/or the central server 120 (or other appropriatecomputing entity) can determine or retrieve estimated travel times forthe specific street segments, geofenced areas, geographic areas, and/orthe like.

Continuing with the above example, if a user requests information abouttraveling from point A (1201 Peachtree Street Northeast, Atlanta, Ga.30309) to point B (4199 Paces Ferry Road SE, Atlanta, Ga. 30339) from amapping-based website/server, the mapping-based website/server or thecentral server 120 can determine or retrieve routing directions(comprising distance data/information), speed information/data (e.g.,current estimated speeds, historical speeds, and/or posted speedlimits), and/or the travel times for the street segments that will betraversed during the travel from point A (1201 Peachtree StreetNortheast, Atlanta, Ga. 30309) to point B (4199 Paces Ferry Road SE,Atlanta, Ga. 30339). As noted, to travel from point A (1201 PeachtreeStreet Northeast, Atlanta, Ga. 30309) to point B (4199 Paces Ferry RoadSE, Atlanta, Ga. 30339), the following may be a route for completing thetravel (shown in FIG. 56).

-   -   Step 1: 1201 Peachtree Street NE, Atlanta, Ga. 30361 traveling        0.0602 miles (381 feet) to 14th Street NE.    -   Step 2: Take the 1st right onto 14th Street NE traveling 0.4        miles to Williams Street NW.    -   Step 3: Turn right onto Williams Street NW traveling 0.2 miles        to 1-75 ramp N.    -   Step 4: Take the ramp on the left onto 1-75 N traveling 6.3        miles to exit 256.    -   Step 5: Take exit 256 toward US-41 traveling 0.2 miles to Mount        Paran Road NW.    -   Step 6: Turn left onto Mount Paran Road NW traveling 0.8 miles        to Paces Ferry Road. NW.    -   Step 7: Turn right onto Paces Ferry Road NW traveling 1.1 miles        to destination (4199 Paces Ferry Road SE, Atlanta, Ga. 30339).

With the route determined and/or the specific streets, street segments,geofenced areas, geographic areas, user-specified criteria, and/or thelike identified, the mapping-based website/server or the central server120 can determine or retrieve the travel times corresponding to thisroute. Such travel times can be determined with or without travel delaysand/or based on current estimated speeds, historical speeds, and/orposted speed limits.

To do so, in one embodiment, the travel time determining module may beconfigured to retrieve or access the posted speed limits associated withthe specific streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria from the central server databasecorresponding to the route for completing the travel. With the postedspeed limits and the routing directions (comprising distancedata/information) corresponding to the route for completing the travel,the central server 120 (or other computing entity) can determine theestimated travel time for completing the travel.

Travel Delays Speed Hours Seconds Limit Cur./Hist. 1201 Peachtree St NE,Atlanta, 0.0097 2.16 35 31 GA. 14th St NE, Atlanta, GA. 0.0125 18 45 28Williams St. NW, Atlanta, GA. 0.0056 3.96 35 15 I-75 N, Atlanta, GA.0.0014 31.68 65 64 Exit 256, Atlanta, GA. 0.0047 3.24 25 23 Mt Paran RdNW, Atlanta, GA. 0.0069 20.16 35 30 Paces Ferry Rd NW, Atlanta, GA.0.0103 40.68 35 29

The travel time (not taking into account travel delays) for specificstreets, street segments, geofenced areas, geographic areas, and/or thelike can be determined from the below equations and as shown in FIG. 59.Travel Time w/o Travel Delays=Distance/SpeedAverage Speed w/o Travel Delays=Distance/Travel Time w/o Travel Delays

Continuing with the above example, as shown in FIG. 59, the totalestimated travel time to travel from point A (1201 Peachtree StreetNortheast, Atlanta, Ga. 30309) to point B (4199 Paces Ferry Road SE,Atlanta, Ga. 30339) based on the posted speed limit (without taking intoaccount travel delays) is estimated at 0.1755 hours or 10 minutes and 53seconds.

In another embodiment, the travel time determining module may beconfigured to retrieve or access the current or historical speedsassociated with the specific streets, street segments, geographic areas,geofenced areas, and/or user-specified criteria from the central serverdatabase corresponding to the route for completing the travel. With thecurrent or historical speeds and the routing directions (comprisingdistance data/information) corresponding to the route for completing thetravel, the central server 120 (or other computing entity) can determinefrom the estimated travel time for completing the travel. The estimatedtravel time (not taking into account travel delays) for specificstreets, street segments, geofenced areas, geographic areas, and/or thelike can be determined. Continuing with the above example, as shown inFIG. 60, the total estimated travel time to travel from point A (1201Peachtree Street Northeast, Atlanta, Ga. 30309) to point B (4199 PacesFerry Road SE, Atlanta, Ga. 30339) based on the current or historicalspeeds (without taking into account travel delays) is estimated at0.2013 hours or 12 minutes and 1 second.

Such travel times can also be determined taking into account traveldelays. To do so, in one embodiment, the travel time determining modulemay be configured to retrieve or access the posted speed limits andtravel delays associated with the specific streets, street segments,geographic areas, geofenced areas, and/or user-specified criteria fromthe central server database corresponding to the route for completingthe travel. With the posted speed limits, the travel delays, and therouting directions (comprising distance data/information) correspondingto the route for completing the travel, the central server 120 (or othercomputing entity) can determine the estimated travel time for completingthe travel.

Travel Delays Speed Distance Hours Seconds Limit Cur./Hist. (M) 1201Peachtree Street 0.0097 2.16 35 31 0.0602 NE, Atlanta, GA. 14th StreetNE, 0.0125 18 45 28 0.4 Atlanta, GA. Williams Street NW, 0.0056 3.96 3515 0.2 Atlanta, GA. I-75 N, Atlanta, GA. 0.0014 31.68 65 64 6.3 Exit256, Atlanta, GA. 0.0047 3.24 25 23 0.2 Mount Paran Road 0.0069 20.16 3530 0.8 NW, Atlanta, GA. Paces Ferry Road NW, 0.0103 40.68 35 29 1.1Atlanta, GA.

The travel time (taking into account travel delays) for specificstreets, street segments, geofenced areas, geographic areas, and/or thelike can be determined from the below equations and as shown in FIGS. 61and 62.Travel Delay for Distance=Travel Delay·DistanceTravel Time w/ Travel Delays=Travel Delay for Distance+Travel Time w/oTravel DelaysTravel Time w/ Travel Delays=Distance/Avg. Speed w/ Travel DelaysAverage Speed w/ Travel Delays=Distance/Travel Time w/ Travel Delays

Continuing with the above example, as shown in FIG. 61, the totalestimated travel time to travel from point A (1201 Peachtree StreetNortheast, Atlanta, Ga. 30309) to point B (4199 Paces Ferry Road SE,Atlanta, Ga. 30339) based on the posted speed limit (and taking intoaccount travel delays) is estimated at 0.2088 hours or 12 minutes and 53seconds.

In another embodiment, the travel time determining module may beconfigured to retrieve or access the current or historical speeds andtravel delays associated with the specific streets, street segments,geographic areas, geofenced areas, and/or user-specified criteria fromthe central server database corresponding to the route for completingthe travel. With the current or historical speeds, travel delays, andthe routing directions (comprising distance data/information)corresponding to the route for completing the travel, the central server120 (or other computing entity) can determine the estimated travel timefor completing the travel. The estimated travel time (taking intoaccount travel delays) for specific streets, street segments, geofencedareas, geographic areas, and/or the like. Continuing with the aboveexample, as shown in FIG. 62, the total estimated travel time to travelfrom point A (1201 Peachtree Street Northeast, Atlanta, Ga. 30309) topoint B (4199 Paces Ferry Road SE, Atlanta, Ga. 30339) based on thecurrent or historical speeds (and taking into account travel delays) isestimated at 0.2345 hours or 14 minutes and 7 seconds.

With estimated travel times determined and the corresponding distance,the central server 120 (or other computing entity) can determine theaverage speed for specific streets, street segments, geofenced areas,geographic areas, and/or the like that takes into account travel delaysusing the below equation.Average Speed w/ Travel Delays=Distance/Travel Time w/ Travel Delays

The average speed with travel delays can be determined regularly,periodically, continuously, and/or in response to certain triggers. Inembodiment, for quicker access, the average speed with travel delays forstreets, street segments, geographic areas, geofenced areas, and/oruser-specified criteria can be stored in association with records forthe same, as previously described (including by days of week and timesof day).

According to various embodiments, the estimated travel times can then beused by or provided to the appropriate computing entity (e.g., centralserver 120, mapping-based website/server, user computing entity orinterface) for display (see FIG. 63) or for use by the user or anotherprogram, for example. In embodiment, for quicker access, estimatedtravel times for streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria can be stored in association withrecords for the same. The determined travel time may be stored as avalue indicative of the corresponding travel time associated with thecorresponding streets, street segments, geographic areas, geofencedareas, and/or user-specified criteria.

Tax, Toll, or Incentive Determination Module

Tax, Toll, or Incentive Determination Module

According to various embodiments, a tax, toll, or incentivedetermination module may be stored on a variety of computing entities.The terms tax, toll, fee, and similar words are used interchangeably. Inone embodiment, the travel time determining module may be generallyconfigured for determining tolls, taxes, incentives, and/or the like forentering, exiting, or accessing an area based at least in part on traveldelays. For example, travel delays may be an indicator of the carbonfootprint, traffic congestion, peak travel times, and/or the like forthe corresponding streets, street segments, geographic areas, and/orgeofenced areas. Thus, to reduce carbon emissions, reduce trafficcongestion, limit travel during peak travel times, and/or the like, thetravel delays may be used by a variety of entities for differentpurposes. For example, a city, county, or state may base toll rates,fuel use taxes, and/or road uses taxes on the travel delays. This mayinvolve the use of a sliding scale, for instance. For example, whentraveling during times of high travel delays, the higher thecorresponding toll or tax may be set by the appropriate computingentity. Similarly, when traveling during times of low travel delays, thelower the corresponding toll or tax may be set by the appropriatecomputing entity. Further, road planning entities may use the traveldelay information to identity traffic congestion trouble spots,bottlenecks, and/or other areas that may require the assistance of theplanners. In yet another embodiment, a city, county, or state mayprovide incentives (e.g., rebates, credits, monetary incentives, and/orthe like) for traveling during times that correspond to low traveldelays for corresponding streets, street segments, geographic areas,geofenced areas, and/or user-specified area.

Further, because the travel delays may correspond to particular times ofday and/or days of the week, the tolls, taxes, incentives, and/or thelike may correspond to the same. For example, the tolls, taxes,incentives, and/or the like may correspond to (1) Holidays: morning(e.g., 6 AM-10 AM), mid-day (e.g., 10 AM-2 PM), afternoon (e.g., 2 PM-5PM), rush-hour (e.g., 5 PM-7 PM), evening (e.g., 7 PM-12 AM), or night(e.g., 12 AM-6 AM); (2) Mondays-Thursdays: morning (e.g., 6 AM-10 AM),mid-day (e.g., 10 AM-2 PM), afternoon (e.g., 2 PM-5 PM), rush-hour(e.g., 5 PM-7 PM), evening (e.g., 7 PM-12 AM), or night (e.g., 12 AM-6AM); (3) Fridays: morning (e.g., 6 AM-10 AM), mid-day (e.g., 10 AM-2PM), afternoon (e.g., 2 PM-5 PM), rush-hour (e.g., 5 PM-7 PM), evening(e.g., 7 PM-12 AM), or night (e.g., 12 AM-6 AM); (4) Saturdays andSundays: morning (e.g., 6 AM-10 AM), mid-day (e.g., 10 AM-2 PM),afternoon (e.g., 2 PM-5 PM), rush-hour (e.g., 5 PM-7 PM), evening (e.g.,7 PM-12 AM), or night (e.g., 12 AM-6 AM). As will be recognized, avariety of other approaches and techniques can be used to adapt tovarious needs and circumstances.

CONCLUSION

As should be appreciated, the embodiments may be implemented in variousways, including as methods, apparatus, systems, or computer programproducts. Accordingly, the embodiments may take the form of an entirelyhardware embodiment or an embodiment in which a processor is programmedto perform certain steps. Furthermore, the various implementations maytake the form of a computer program product on a computer-readablestorage medium having computer-readable program instructions embodied inthe storage medium. Any suitable computer-readable storage medium may beutilized including hard disks, CD-ROMs, optical storage devices, ormagnetic storage devices.

The embodiments are described below with reference to block diagrams andflowchart illustrations of methods, apparatus, systems, and computerprogram products. It should be understood that each block of the blockdiagrams and flowchart illustrations, respectively, may be implementedin part by computer program instructions, e.g., as logical steps oroperations executing on a processor in a computing system. Thesecomputer program instructions may be loaded onto a computer, such as aspecial purpose computer or other programmable data processing apparatusto produce a specifically-configured machine, such that the instructionswhich execute on the computer or other programmable data processingapparatus implement the functions specified in the flowchart block orblocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including computer-readableinstructions for implementing the functionality specified in theflowchart block or blocks. The computer program instructions may also beloaded onto a computer or other programmable data processing apparatusto cause a series of operational steps to be performed on the computeror other programmable apparatus to produce a computer-implementedprocess such that the instructions that execute on the computer or otherprogrammable apparatus provide operations for implementing the functionsspecified in the flowchart block or blocks.

Accordingly, blocks of the block diagrams and flowchart illustrationssupport various combinations for performing the specified functions,combinations of operations for performing the specified functions andprogram instructions for performing the specified functions. It shouldalso be understood that each block of the block diagrams and flowchartillustrations, and combinations of blocks in the block diagrams andflowchart illustrations, can be implemented by special purposehardware-based computer systems that perform the specified functions oroperations, or combinations of special purpose hardware and computerinstructions.

Many modifications and other embodiments of the inventions set forthherein will come to mind to one skilled in the art to which theseembodiments of the invention pertain having the benefit of the teachingspresented in the foregoing descriptions and the associated drawings.Therefore, it is to be understood that the embodiments of the inventionare not to be limited to the specific embodiments disclosed and thatmodifications and other embodiments are intended to be included withinthe scope of the appended claims. Although specific terms are employedherein, they are used in a generic and descriptive sense only and notfor purposes of limitation.

The invention claimed is:
 1. A method for determining an average speed,the method comprising: identifying, via one or more processors, timeinformation and distance information associated with traveling from afirst location to a second location; identifying, via the one or moreprocessors, travel delay information associated with traveling from thefirst location to the second location, wherein (a) the travel delayinformation comprises a value indicative of the average amount of traveldelay time per unit of distance associated with a geographical area and(b) the value indicative of the average amount of travel delay time perunit of distance associated with the geographical area is determined by(i) determining a distance traveled by a vehicle within the geographicalarea during one or more time periods as indicated by operational datacomprising vehicle telematics data, (ii) identifying one or more traveldelay segments during the one or more time periods, (iii) determining aduration of the one or more travel delay segments, and (iv) determining,based at least in part on the distance traveled and the duration of theone or more travel delay segments, the value indicative of the averageamount of travel delay time per unit of distance associated with thegeographical area; and determining, via the one or more processors, anaverage speed for traveling from the first location to the secondlocation based at least in part on the time information, the distanceinformation, and the travel delay information.
 2. The method of claim 1,wherein the travel delay information comprises a value indicative of anaverage amount of travel delay time per unit of distance associated withat least one of the first location or the second location.
 3. The methodof claim 1, wherein the travel delay segments each represent a period ofengine idle time occurring while the vehicle was traveling.
 4. Themethod of claim 1, wherein the value indicative of the average amount oftravel delay time per unit of distance comprises a travel delay secondsper mile traveled value.
 5. The method of claim 1, wherein the valueindicative of the average amount of travel delay time per unit ofdistance comprises a miles traveled per travel delay minute value. 6.The method of claim 1, wherein the travel delay segments are identifiedby: segmenting the operational data into a plurality of activitysegments representing periods of time classified according to vehicleactivity or service activity, the activity segments comprising start oftrip segments, travel segments, and end of trip segments; andidentifying, based on the operational data, segments of engine idle timeoccurring during one of the travel segments and designating theidentified engine idle segments as travel delay segments.
 7. Anapparatus comprising at least one processor and at least one memoryincluding computer program code, the at least one memory and thecomputer program code configured to, with the processor, cause theapparatus to at least: identify time information and distanceinformation associated with traveling from a first location to a secondlocation; identify travel delay information associated with travelingfrom the first location to the second location, wherein (a) the traveldelay information comprises a value indicative of the average amount oftravel delay time per unit of distance associated with a geographicalarea and (b) the value indicative of the average amount of travel delaytime per unit of distance associated with the geographical area isdetermined by (i) determining a distance traveled by a vehicle withinthe geographical area during one or more time periods as indicated byoperational data comprising vehicle telematics data, (ii) identifyingone or more travel delay segments during the one or more time periods,(iii) determining a duration of the one or more travel delay segments,and (iv) determining, based at least in part on the distance traveledand the duration of the one or more travel delay segments, the valueindicative of the average amount of travel delay time per unit ofdistance associated with the geographical area; and determine an averagespeed for traveling from the first location to the second location basedat least in part on the time information, the distance information, andthe travel delay information.
 8. The apparatus of claim 7, wherein thetravel delay information comprises a value indicative of an averageamount of travel delay time per unit of distance associated with atleast one of the first location or the second location.
 9. The apparatusof claim 7, wherein the travel delay segments each represent a period ofengine idle time occurring while the vehicle was traveling.
 10. Theapparatus of claim 7, wherein the value indicative of the average amountof travel delay time per unit of distance comprises a travel delayseconds per mile traveled value.
 11. The apparatus of claim 7, whereinthe value indicative of the average amount of travel delay time per unitof distance comprises a miles traveled per travel delay minute value.12. The apparatus of claim 7, wherein the travel delay segments areidentified by the apparatus by: segmenting the operational data into aplurality of activity segments representing periods of time classifiedaccording to vehicle activity or service activity, the activity segmentscomprising start of trip segments, travel segments, and end of tripsegments; and identifying, based on the operational data, segments ofengine idle time occurring during one of the travel segments anddesignating the identified engine idle segments as travel delaysegments.
 13. A computer program product for determining an averagespeed, the computer program product comprising at least onenon-transitory computer-readable storage medium having computer-readableprogram code portions stored therein, the computer-readable program codeportions comprising: an executable portion configured to identify timeinformation and distance information associated with traveling from afirst location to a second location; an executable portion configured toidentify travel delay information associated with traveling from thefirst location to the second location, wherein (a) the travel delayinformation comprises a value indicative of the average amount of traveldelay time per unit of distance associated with a geographical area and(b) the value indicative of the average amount of travel delay time perunit of distance associated with the geographical area is determined by(i) determining a distance traveled by a vehicle within the geographicalarea during one or more time periods as indicated by operational datacomprising vehicle telematics data, (ii) identifying one or more traveldelay segments during the one or more time periods, (iii) determining aduration of the one or more travel delay segments, and (iv) determining,based at least in part on the distance traveled and the duration of theone or more travel delay segments, the value indicative of the averageamount of travel delay time per unit of distance associated with thegeographical area; and an executable portion configured to determine anaverage speed for traveling from the first location to the secondlocation based at least in part on the time information, the distanceinformation, and the travel delay information.
 14. The computer programproduct of claim 13, wherein the travel delay information comprises avalue indicative of an average amount of travel delay time per unit ofdistance associated with at least one of the first location or thesecond location.
 15. The computer program product of claim 13, whereinthe travel delay segments each represent a period of engine idle timeoccurring while the vehicle was traveling.
 16. The computer programproduct of claim 13, wherein the value indicative of the average amountof travel delay time per unit of distance comprises a travel delayseconds per mile traveled value.
 17. The computer program product ofclaim 13, wherein the value indicative of the average amount of traveldelay time per unit of distance comprises a miles traveled per traveldelay minute value.
 18. The computer program product of claim 13,wherein the travel delay segments are identified by the computer programproduct by: segmenting the operational data into a plurality of activitysegments representing periods of time classified according to vehicleactivity or service activity, the activity segments comprising start oftrip segments, travel segments, and end of trip segments; andidentifying, based on the operational data, segments of engine idle timeoccurring during one of the travel segments and designating theidentified engine idle segments as travel delay segments.